Reinhard Furrer's Publications and Proceedings

[ 2021 | 2019 |2017 | 2015 | 2013 | 2011 | 2009 | 2007 | pre 2005 ]

View publications and publication metrics on orcid.org/0000-0002-6319-2332 ZORA

indicates Open Access, Free PDF, Open Archive etc. Articles pre 2015 are not tagged ( links to arXiv.org, links to bioRxiv.org).

Forthcoming

2024

	Graff, A., Lischka, M., Zakharko, T., Furrer, R. and Bickel, B. (2024). densify: An R package to reduce empty cells in data frames of typological linguistic data. Journal of Open Source Software, 9(101), 7024. [Summary] [BibTeX] [Github Repo]
	Summary: The R package densify provides a procedure to prune input data frames containing empty cells (or cells with values {?} or {NA}) to denser sub-matrices with fewer empty cells. The pruning process trades off a series of variably weighted concerns, including data retention, coding density (proportion of non-empty cells) and taxonomic diversity of rows (representing for example phylogenetic relations). Users can adapt the relative weights given to these concerns through various parameters so that the densification process best fits their needs. As such, the software is useful for several purposes, including the densification of sparse input matrices and the subsampling of large input matrices according to a procedure that is sensitive to taxonomic structure.
	BibTeX: @ARTICLE{Graf:etal:24, AUTHOR = {Anna Graff and Marc Lischka and Taras Zakharko and Reinhard Furrer and Balthasar Bickel}, TITLE = {densify: An R package to reduce empty cells in data frames of typological linguistic data}, JOURNAL = {JOSS}, FJOURNAL = {Journal of Open Source Software}, YEAR = {2023}, DOI = {10.21105/joss.07024}, VOLUME = {9}, NUMBER = {101}, PAGES = {7024}, ARXIV = {https://arxiv.org/abs/2007.14684}, FUNDING = {-}, DISPLAY = {Graff, A., Lischka, M., Zakharko, T., Furrer, R. and Bickel, B. (2024). densify: An R package to reduce empty cells in data frames of typological linguistic data.. Journal of Open Source Software, 9(101), 7024.}, }
	Faouzi, T., Furrer, R. and Porcu, E. (2024). Compatibility of Space-Time Kernels with Full, Dynamical, or Compact Support. Mathematical Methods in the Applied Sciences, 1–10. [Abstract] [BibTeX] [Shiny illustration]
	Abstract: This paper deals with compatibility of space-time kernels with (either) full, spatially dynamical, or space-time compact support. We deal with the dilemma of statistical accuracy versus computational scalability, which are in a notorious trade-off. Apparently, models with full support ensure maximal information but are computationally expensive, while compactly supported models achieve computational scalability at the expense of loss of information. Hence, an inspection of whether these models might be compatible is necessary. The criterion we use for such an inspection is based on equivalence of Gaussian measures. We provide sufficient conditions for space-time compatibility. As a corollary, we deduce implications in terms of maximum likelihood estimation and misspecified kriging prediction under fixed domain asymptotics. Some results of independent interest relate about the space-time spectrum associated with the classes of kernels proposed in the paper. Keywords: Fixed-domain asymptotics, Microergodic parameter, Matérn Covariance, Maximum likelihood, Space-Time Generalized Wendland family, Prediction
	BibTeX: @ARTICLE{Faou:Furr:Porc:24, AUTHOR = {Tarik Faouzi and Reinhard Furrer and Emilio Porcu}, TITLE = {Compatibility of space-time kernels with full, dynamical, or compact support}, JOURNAL = {Math. Meth. Appl. Sci.}, FJOURNAL = {Mathematical Methods in the Applied Sciences}, YEAR = {2024}, DOI = {10.1002/mma.10379}, VOLUME = {}, NUMBER = {}, PAGES = {1--10}, ARXIV = {https://arxiv.org/abs/2007.14684}, FUNDING = {SNSF-175529, and more}, DISPLAY = {Faouzi, T., Furrer, R. and Porcu, E. (2024). Compatibility of Space-Time Kernels with Full, Dynamical, or Compact Support. Mathematical Methods in the Applied Sciences, 1–10.}, }
	Furrer, R. and Hediger, M. (2024). On the orthogonality of zero-mean Gaussian measures: Sufficiently dense sampling. Stochastic Processes and their Applications, 173, 104356. [Abstract] [BibTeX]
	Abstract: For a stationary random function 𝜉, sampled on a subset 𝐷 of R^𝑑 , we examine the equivalence and orthogonality of two zero-mean Gaussian measures P1 and P2 associated with 𝜉. We give the isotropic analog to the result that the equivalence of P1 and P2 is linked with the existence of a square-integrable extension of the difference between the covariance functions of P1 and P2 from 𝐷 to R^𝑑 . We show that the orthogonality of P1 and P2 can be recovered when the set of distances from points of 𝐷 to the origin is dense in the set of non-negative real numbers. Keywords: Gaussian random fields, Stationarity, Isotropy, Equivalence of Gaussian measures, Orthogonality of Gaussian measures
	BibTeX: @ARTICLE{Furr:Hedi:24, AUTHOR = {Furrer, R. and Hediger, M.}, TITLE = {On the orthogonality of zero-mean Gaussian measures: Sufficiently dense sampling}, JOURNAL = {Stoch. Proc. Appl.}, FJOURNAL = {Stochastic Processes and their Applications}, YEAR = {2024}, DOI = {10.1016/j.spa.2024.104356}, VOLUME = {173}, PAGES = {104356}, ARXIV = {https://arxiv.org/abs/2212.10239v2}, FUNDING = {SNSF-175529}, DISPLAY = {Furrer, R. and Hediger, M. (2024). On the orthogonality of zero-mean Gaussian measures: Sufficiently dense sampling. Stochastic Processes and their Applications, 173, 104356.}, }
	Muñoz-Gómez, V., Furrer, R., Yin, J., Shaw, A. P. M., Rasmussen, P. and Torgerson, P. R. (2024). Prediction of coccidiosis prevalence in extensive backyard chickens in countries and regions of the Horn of Africa. Veterinary Parasitology, 327, 110143. [Abstract] [BibTeX]
	Abstract: Coccidiosis is one of the leading morbidity causes in chickens, causing a reduction of body weight and egg production. Backyard chickens are at risk of developing clinical and subclinical coccidiosis due to outdoor housing and scavenging behaviour, jeopardizing food security in households. The objectives of this study were to estimate clinical prevalence of coccidiosis at country and regional levels in the Horn of Africa in extensive backyard chickens. A binomial random effects model was developed to impute prevalence of coccidiosis. Previously gathered prevalence data (n = 40) in backyard chickens was used to define the model. Precipitation (OR: 1.09 (95% CI: 1.05–1.13) and the presence of seasonal rainfall (OR: 1.85, 95% CI: 1.27–2.70) significantly increase prevalence. Results showed an overall prevalence of coccidiosis in the Horn of Africa of 0.21 (95% CI: 0.15–0.29). Ethiopia, the Republic of South Sudan and Kenya showed the highest prevalence and Djibouti the lowest. Significant differences between Djibouti and the countries with highest prevalence were found. However, no evidence of a significant difference between the rest of the countries. Kenya and Ethiopia showed larger prevalence differences between regions. Results could assist with the targeting of testing for coccidiosis, the observation for clinical disease of chickens living in specific regions and as a baseline for the evaluation of future control measures. Keywords: Coccidiosis; Chicken; Backyard; Imputation; Climate; Horn of Africa
	BibTeX: @ARTICLE{Muno:Furr:etal:24, AUTHOR = {Violeta Muñoz-Gómez and Reinhard Furrer and Jie Yin and Alexandra PM Shaw and Philip Rasmussen and Paul R. Torgerson}, TITLE = {Prediction of coccidiosis prevalence in extensive backyard chickens in countries and regions of the Horn of Africa}, JOURNAL = {Vet. Parasitol.}, FJOURNAL = {Veterinary Parasitology}, YEAR = {2024}, DOI = {10.1016/j.vetpar.2024.110143}, VOLUME = {327}, NUMBER = {}, PAGES = {110143}, FUNDING = {div}, DISPLAY = {Muñoz-Gómez, V., Furrer, R., Yin, J., Shaw, A. P. M., Rasmussen, P. and Torgerson, P. R. (2024). Prediction of coccidiosis prevalence in extensive backyard chickens in countries and regions of the Horn of Africa. Veterinary Parasitology, 327, 110143.}, }

2023

	Furrer, R. and Hediger, M. (2023). Asymptotic analysis of ML-covariance parameter estimators based on covariance approximations. Electronic Journal of Statistics, 17(2), 3050–31021. [Abstract] [BibTeX]
	Abstract: Given a zero-mean Gaussian random field with a covariance function that belongs to a parametric family of covariance functions, we introduce a new notion of likelihood approximations, termed truncated-likelihood functions. Truncated-likelihood functions are based on direct functional approximations of the presumed family of covariance functions. For compactly supported covariance functions, within an increasing-domain asymptotic framework, we provide sufficient conditions under which consistency and asymptotic normality of estimators based on truncated-likelihood functions are preserved. We apply our result to the family of generalized Wendland covariance functions and discuss several examples of Wendland approximations. For families of covariance functions that are not compactly supported, we combine our results with the covariance tapering approach and show that ML estimators, based on truncated-tapered likelihood functions, asymptotically minimize the Kullback-Leibler divergence, when the taper range is fixed. Keywords: asymptotic normality, compactly supported covariance functions, consistency, covariance tapering, Gaussian random fields, Likelihood approximations
	BibTeX: @ARTICLE{Furr::Hedi:23, AUTHOR = {Reinhard Furrer and Michael Hediger}, TITLE = {Asymptotic analysis of {ML}-covariance parameter estimators based on covariance approximations}, JOURNAL = {Electron. J. Statist.}, FJOURNAL = {Electronic Journal of Statistics}, YEAR = {2023}, VOLUME = {17}, NUMBER = {2}, PAGES = {3050-3102}, ISSN = {1935-7524}, DOI = {10.1214/23-EJS2170}, ARXIV = {https://arxiv.org/abs/2112.12317}, FUNDING = {SNSF-175529}, DISPLAY = {Furrer, R. and Hediger, M. (2023). Asymptotic analysis of ML-covariance parameter estimators based on covariance approximations. Electronic Journal of Statistics, 17(2), 3050–31021.}, }
	Kalischek, N., Daudt, R. C., Peters, T., Furrer, R., Jan D. Wegner, J. D. and Schindler, K. (2023). BiasBed - Rigorous Texture Bias Evaluation. 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 22221–22230. [Abstract] [BibTeX] [Code (Github)]
	Abstract: The well-documented presence of texture bias in modern convolutional neural networks has led to a plethora of algorithms that promote an emphasis on shape cues, often to support generalization to new domains. Yet, common datasets, benchmarks and general model selection strategies are missing, and there is no agreed, rigorous evaluation protocol. In this paper, we investigate difficulties and limitations when training networks with reduced texture bias. In particular, we also show that proper evaluation and meaningful comparisons between methods are not trivial. We introduce BiasBed, a testbed for texture- and style-biased training, including multiple datasets and a range of existing algorithms. It comes with an extensive evaluation protocol that includes rigorous hypothesis testing to gauge the significance of the results, despite the considerable training instability of some style bias methods. Our extensive experiments, shed new light on the need for careful, statistically founded evaluation protocols for style bias (and beyond). E.g., we find that some algorithms proposed in the literature do not significantly mitigate the impact of style bias at all. With the release of BiasBed, we hope to foster a common understanding of consistent and meaningful comparisons, and consequently faster progress towards learning methods free of texture bias. Code is available at https://github.com/D1noFuzi/BiasBed. Keywords: training; learning systems; computer vision; protocols; codes; shape; drives.
	BibTeX: @INPROCEEDINGS{Kali:etal:Schi:23, AUTHOR = {Nikolai Kalischek and Rodrigo Caye Daudt and Torben Peters and Reinhard Furrer and Jan D. Wegner and Konrad Schindler}, TITLE = {BiasBed - Rigorous Texture Bias Evaluation}, BOOKTITLE = {2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, YEAR = {2023}, DOI = {10.1109/CVPR52729.2023.02128}, PAGES = {22221-22230}, ARXIV = {https://arxiv.org/abs/2211.13190}, FUNDING = {div}, DISPLAY = {Kalischek, N., Daudt, R. C., Peters, T., Furrer, R., Jan D. Wegner, J. D. and Schindler, K. (2023). BiasBed - Rigorous Texture Bias Evaluation. 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 22221–22230. }, }
	Bodenhausen, N., Hess, J., Valzano, A., Deslandes-Hérold, G., Waelchli, J., Furrer, R., van der Heijden, M. G. A., and Schlaeppi, K. (2023). Predicting soil fungal communities from chemical and physical properties. Journal of Sustainable Agriculture and Environment, 2(3), 225–237. [Abstract] [BibTeX]
	Abstract: Introduction Biogeography describes spatial patterns of diversity and explains why organisms occur in given conditions. While it is well established that the diversity of soil microbes is largely controlled by edaphic environmental variables, microbiome community prediction from soil properties has received less attention. In this study, we specifically investigated whether it is possible to predict the composition of soil fungal communities based on physicochemical soil data using multivariate ordination. Materials and Methods We sampled soil from 59 arable fields in Switzerland and assembled paired data of physicochemical soil properties as well as profiles of soil fungal communities. Fungal communities were characterized using long-read sequencing of the entire ribosomal internal transcribed spacer. We used redundancy analysis to combine the physical and chemical soil measurements with the fungal community data. Results We identified a reduced set of 10 soil properties that explained fungal community composition. Soil properties with the strongest impact on the fungal community included pH, potassium and sand content. Finally, we evaluated the model for its suitability for prediction using leave-one-out validation. The prediction of community composition was successful for most soils, and only 3/59 soils could not be well predicted (Pearson correlation coefficients between observed and predicted communities of <0.5). Further, we successfully validated our prediction approach with a publicly available data set. With both data sets, prediction was less successful for soils characterized by very unique properties or diverging fungal communities, while it was successful for soils with similar characteristics and microbiome. Conclusions Reliable prediction of microbial communities from chemical soil properties could bypass the complex and laborious sequencing-based generation of microbiota data, thereby making soil microbiome information available for agricultural purposes such as pathogen monitoring, field inoculation or yield projections.
	BibTeX: @ARTICLE{Bode:etal:23, AUTHOR = {Bodenhausen, Natacha and Hess, Julia and Valzano, Alain and Deslandes-Hérold, Gabriel and Waelchli, Jan and Furrer, Reinhard and van der Heijden, Marcel G. A. and Schlaeppi, Klaus}, TITLE = {Predicting soil fungal communities from chemical and physical properties}, JOURNAL = {J. Sustain. Agric. Environ}, FJOURNAL = {Journal of Sustainable Agriculture and Environment}, YEAR = {2023}, DOI = {10.1002/sae2.12055}, VOLUME = {2}, NUMBER = {3}, PAGES = {225--237}, FUNDING = {div}, DISPLAY = {Bodenhausen, N., Hess, J., Valzano, A., Deslandes-Hérold, G., Waelchli, J., Furrer, R., van der Heijden, M. G. A., and Schlaeppi, K. (2023). Predicting soil fungal communities from chemical and physical properties. Journal of Sustainable Agriculture and Environment, 2(3), 225–237.}, }
	Rocchini, D., Nowosad, J., D’Introno, R., Chieffallo, L., Bacaro, G., Gatti, R. C. Foody, G. M. Furrer, R., Gábor, L., Malavasi, M., Marcantonio, M., Marchetto, E., Moudrý, V., Ricotta, C., Šímová, P., Torresani, M. and Thouverai, E. (2023). Scientific maps should reach everyone: The cblindplot R package to let colour blind people visualise spatial patterns. Ecological Informatics, 76, 102045. [Abstract] [BibTeX] [Git Repo]
	Abstract: Maps represent powerful tools to show the spatial variation of a variable in a straightforward manner. A crucial aspect in map rendering for its interpretation by users is the gamut of colours used for displaying data. One part of this problem is linked to the proportion of the human population that is colour blind and, therefore, highly sensitive to colour palette selection. The aim of this paper is to present the cblindplot R package and its founding function - cblind.plot() - which enables colour blind people to just enter an image in a coding workflow, simply set their colour blind deficiency type, and immediately get as output a colour blind friendly plot. We will first describe in detail colour blind problems, and then show a step by step example of the function being proposed. While examples exist to provide colour blind people with proper colour palettes, in such cases (i) the workflow include a separate import of the image and the application of a set of colour ramp palettes and (ii) albeit being well documented, there are many steps to be done before plotting an image with a colour blind friendly ramp palette. The function described in this paper, on the contrary, allows to (i) automatically call the image inside the function without any initial import step and (ii) explicitly refer to the colour blind deficiency type being experienced, to further automatically apply the proper colour ramp palette. Keywords: Colour blindness, Computational ecology, Ecological informatics, Mapping, R, Scientific communication
	BibTeX: @ARTICLE{Rocc:etal:23, AUTHOR = {Duccio Rocchini and Jakub Nowosad and Rossella D’Introno and Ludovico Chieffallo and Giovanni Bacaro and Roberto Cazzolla Gatti and Giles M. Foody and Reinhard Furrer and Lukáš Gábor and Marco Malavasi and Matteo Marcantonio and Elisa Marchetto and Vítězslav Moudrý and Carlo Ricotta and Petra Šímová and Michele Torresani and Elisa Thouverai}, TITLE = {Scientific maps should reach everyone: The cblindplot {R} package to let colour blind people visualise spatial patterns}, JOURNAL = {Ecol. Inform.}, FJOURNAL = {Ecological Informatics}, YEAR = {2023}, DOI = {10.1016/j.ecoinf.2023.102045}, VOLUME = {76}, PAGES = {102045}, ARXIV = {}, FUNDING = {SNSF-175529 and more}, DISPLAY = {Rocchini, D., Nowosad, J., D’Introno, R., Chieffallo, L., Bacaro, G., Gatti, R. C. Foody, G. M. Furrer, R., Gábor, L., Malavasi, M., Marcantonio, M., Marchetto, E., Moudrý, V., Ricotta, C., Šímová, P., Torresani, M. and Thouverai, E. (2023). Scientific maps should reach everyone: The cblindplot R package to let colour blind people visualise spatial patterns. Ecological Informatics, 76, 102045.}, }
	Thouverai, E., Marcantonio M., Lenoir, J., Mariasole Galfré, M., Marchetto, E., et al. (2023). Integrals of life: tracking ecosystem spatial heterogeneity from space through the area under the curve of the parametric Rao's Q index. Ecological Complexity, 52, 101029. [Abstract] [BibTeX]
	Abstract: Spatio-ecological heterogeneity is strongly linked to many ecological processes and functions such as plant species diversity patterns and change, metapopulation dynamics, and gene flow. Remote sensing is particularly useful for measuring spatial heterogeneity of ecosystems over wide regions with repeated measurements in space and time. Besides, developing free and open source algorithms for ecological modelling from space is vital to allow to prove workflows of analysis reproducible. From this point of view, NASA developed programs like the Surface Biology and Geology (SBG) to support the development of algorithms for exploiting spaceborne remotely sensed data to provide a relatively fast but accurate estimate of ecological properties in vast areas over time. Most of the indices to measure heterogeneity from space are point descriptors : they catch only part of the whole heterogeneity spectrum. Under the SBG umbrella, in this paper we provide a new R function part of the rasterdiv R package which allows to calculate spatio-ecological heterogeneity and its variation over time by considering all its possible facets. The new function was tested on two different case studies, on multi- and hyperspectral images, proving to be an effective tool to measure heterogeneity and detect its changes over time. Keywords: Biodiversity, Ecological informatics, Modelling, Remote sensing, Satellite imagery
	BibTeX: @ARTICLE{Thou:etal:23, AUTHOR = {Elisa Thouverai and Matteo Marcantonio and Jonathan Lenoir and Mariasole Galfré and Elisa Marchetto and Giovanni Bacaro and Roberto {Cazzolla Gatti} and Daniele {Da Re} and Michele {Di Musciano} and Reinhard Furrer and Marco Malavasi and Vítězslav Moudrý and Jakub Nowosad and Franco Pedrotti and Raffaele Pelorosso and Giovanna Pezzi and Petra Šímová and Carlo Ricotta and Sonia Silvestri and Enrico Tordoni and Michele Torresani and Giorgio Vacchiano and Piero Zannini and Duccio Rocchini}, TITLE = {Integrals of life: tracking ecosystem spatial heterogeneity from space through the area under the curve of the parametric {Rao's Q} index}, JOURNAL = {Ecol. Complex.}, FJOURNAL = {Ecological Complexity}, YEAR = {2023}, DOI = {10.1016/j.ecocom.2023.101029}, VOLUME = {52}, PAGES = {101029}, FUNDING = {SNSF-175529 and others}, DISPLAY = {Thouverai, E., Marcantonio M., Lenoir, J., Mariasole Galfré, M., Marchetto, E., et al. (2023). Integrals of life: tracking ecosystem spatial heterogeneity from space through the area under the curve of the parametric Rao's Q index. Ecological Complexity, 52, 101029. }, }
	Kratzer, G., Lewis, F., Comin, A., Pittavino, M. and Furrer, R. (2023). Additive Bayesian Network Modelling with the R Package abn. Journal of Statistical Software, 105(1), 1–41. [Abstract] [BibTeX] [R package abn] [Replication materials]
	Abstract: The R package abn is designed to fit additive Bayesian network models to observational datasets and contains routines to score Bayesian networks based on Bayesian or information theoretic formulations of generalized linear models. It is equipped with exact search and greedy search algorithms to select the best network, and supports continuous, discrete and count data in the same model and input of prior knowledge at a structural level. The Bayesian implementation supports random effects to control for one-layer clustering. In this paper, we give an overview of the methodology and illustrate the package’s functionality using a veterinary dataset concerned with respiratory diseases in commercial swine production. Keywords: structure learning, graphical models, greedy search, exact search, scoring algo- rithm, GLM, graph theory.
	BibTeX: @ARTICLE{Krat:etal:Furr:22, AUTHOR = {Kratzer, G. and Lewis, F. and Comin, A. and Pittavino, M. and Furrer, R.}, TITLE = {Additive Bayesian Network Modelling with the {R} Package abn}, JOURNAL = {J. Stat. Softw.}, FJOURNAL = {Journal of Statistical Software}, YEAR = {2022}, DOI = {10.18637/jss.v105.i08}, VOLUME = {105}, NUMBER = {1}, PAGES = {1--41}, DISPLAY = {Kratzer, G., Lewis, F., Comin, A., Pittavino, M. and Furrer, R. (2023). Additive Bayesian Network Modelling with the R Package abn. Journal of Statistical Software, 105(1), 1–41.}, }

2022

	Schuh, L. A., Santos, M. J., Schaepman, M. E. and Furrer, R. (2022). An Empirical Bayesian Approach to Quantify Multi-Scale Spatial Structural Diversity in Remote Sensing Data. Remote Sensing, 15, 14. [Abstract] [BibTeX] [Git Repo] [Data] [R Package]
	Abstract: Landscape structure is as much a driver as a product of environmental and biological interactions and it manifests as scale-specific, but also as multi-scale patterns. Multi-scale structure affects processes on smaller and larger scales and its detection requires information from different scales to be combined. Herein, we propose a novel method to quantify multi-scale spatial structural diversity in continuous remote sensing data. We combined information from different extents with an empirical Bayesian model and we applied a new entropy metric and a value co-occurrence approach to capture heterogeneity. We tested this method on Normalized Difference Vegetation Index data in northern Eurasia and on simulated data and we also tested the effect of coarser pixel resolution. We find that multi-scale structural diversity can reveal itself as patches and linear landscape features, which persist or become apparent across spatial scales. Multi-scale line features reveal the transition zones between spatial regimes and multi-scale patches reveal those areas within transition zones where values are most different from each other. Additionally, spatial regimes themselves can be distinguished. We also find the choice of scale need not be informed by typical length-scales, which makes the method easy to implement. The proposed multi-scale approach can be applied to other contexts, following the roadmap we pave out in this study and using the tools available in the accompanying R package StrucDiv. Keywords: multi-scale landscape features; spatial structural diversity; empirical Bayesian model; structural diversity entropy; landscape patterns
	BibTeX: @ARTICLE{Schu:etal:Furr:22, AUTHOR = {Schuh, L. A. and Santos, M. J. and Schaepman, M. E. and Furrer, R.}, TITLE = {An Empirical {B}ayesian Approach to Quantify Multi-Scale Spatial Structural Diversity in Remote Sensing Data}, JOURNAL = {Remote Sensing}, FJOURNAL = {}, YEAR = {2022}, DOI = {10.3390/rs15010014}, VOLUME = {15}, PAGES = {14}, FUNDING = {URPP}, DISPLAY = {Schuh, L. A., Santos, M. J., Schaepman, M. E. and Furrer, R. (2022). An Empirical Bayesian Approach to Quantify Multi-Scale Spatial Structural Diversity in Remote Sensing Data. Remote Sensing, 15, 14.}, }
	Flury, R. and Furrer, R. (2022). Pipeline to Identify Dominant Features in Spatial Data. Journal of Computational Mathematics and Data Science, 5, 100063. [Abstract] [BibTeX] [Git Repo]
	Abstract: Dominant-feature identification decomposes spatial data into several additive components to make different features apparent on each component. It recognizes their dominant features credibly and assesses feature attributes. This paper describes the pipeline to apply this method to regular and irregular lattice data as well as geostatistical data. These implementations are all openly available and templates for each case are provided in an associated git repository. As geostatistical data is typically large, we propose several efficient approximations suitable for such data. Emphasizing the use of these approximations in the context of dominant-feature identification, we apply them to data from a climate model describing the monthly mean diurnal range for the period between the years 2081 and 2100. Keywords: Multi-scale process, multiresolution decomposition, geostatistical data, climate models.
	BibTeX: @ARTICLE{Flur:Furr:22, AUTHOR = {Roman Flury and Reinhard Furrer}, TITLE = {Pipeline to Identify Dominant Features in Spatial Data}, JOURNAL = {JCMDS}, FJOURNAL = {Journal of Computational Mathematics and Data Science}, YEAR = {2022}, DOI = {10.1016/j.jcmds.2022.100063}, VOLUME = {5}, PAGES = {100063}, FUNDING = {SNSF-175529}, DISPLAY = {Flury, R. and Furrer, R. (2022). Pipeline to Identify Dominant Features in Spatial Data. Journal of Computational Mathematics and Data Science, 5, 100063.}, }
	Bachoc, F., Porcu, E., Bevilacqua, M., Furrer, R. and Faouzi, T. (2022). Asymptotically Equivalent Prediction in Multivariate Geostatistics. Bernoulli, 28(4), 2518–2545. [Abstract] [BibTeX]
	Abstract: Cokriging is the common method of spatial interpolation (best linear unbiased prediction) in multivariate geostatistics. While best linear prediction has been well understood in univariate spatial statistics, the literature for the multivariate case has been elusive so far. The new challenges provided by modern spatial datasets, being typically multivariate, call for a deeper study of cokriging. In particular, we deal with the problem of misspecified cokriging prediction within the framework of fixed domain asymptotics. Specifically, we provide conditions for equivalence of measures associated with multivariate Gaussian random fields, with index set in a compact set of a d-dimensional Euclidean space. Such conditions have been elusive for over about 50 years of spatial statistics. We then focus on the multivariate Matérn and Generalized Wendland classes of matrix valued covariance functions, that have been very popular for having parameters that are crucial to spatial interpolation, and that control the mean square differentiability of the associated Gaussian process. We provide sufficient conditions, for equivalence of Gaussian measures, relying on the covariance parameters of these two classes. This enables to identify the parameters that are crucial to asymptotically equivalent interpolation in multivariate geostatistics. Our findings are then illustrated through simulation studies. Keywords: Cokriging; Equivalence of Gaussian Measures; Fixed Domain Asymptotics; Functional Analysis; Generalized Wendland; Matérn; Spectral Analysis
	BibTeX: @ARTICLE{Bach:etal:22, AUTHOR = {Francois Bachoc and Emilio Porcu and Moreno Bevilacqua and Reinhard Furrer and Tarik Faouzi}, TITLE = {Asymptotically Equivalent Prediction in Multivariate Geostatistics}, JOURNAL = {Bernoulli}, FJOURNAL = {Bernoulli}, YEAR = {2022}, DOI = {10.3150/21-BEJ1427}, VOLUME = {28}, NUMBER = {4}, PAGES = {2518--2545}, ARXIV = {https://arxiv.org/abs/2007.14684}, FUNDING = {SNSF-175529 and more}, DISPLAY = {Bachoc, F., Porcu, E., Bevilacqua, M., Furrer, R. and Faouzi, T. (2022). Asymptotically Equivalent Prediction in Multivariate Geostatistics. Bernoulli, 28(4), 2518–2545.}, }
	Dambon J. A., Sigrist, F. and Furrer, R. (2022). Joint variable selection of both fixed and random effects for Gaussian process-based spatially varying coefficient models. International Journal of Geographical Information Science, 36(12), 2525–2548. [Abstract] [BibTeX] [Code]
	Abstract: Spatially varying coefficient (SVC) models are a type of regression models for spatial data where covariate effects vary over space. If there are several covariates, a natural question is which covariates have a spatially varying effect and which not. We present a new variable selection approach for Gaussian process-based SVC models. It relies on a penalized maximum likelihood estimation and allows joint variable selection both with respect to fixed effects and Gaussian process random effects. We validate our approach in a simulation study as well as a real world data set. In the simulation study, the penalized maximum likelihood estimation correctly identifies zero fixed and random effects, while the penalty-induced bias of non-zero estimates is negligible. In the real data application, our proposed penalized maximum likelihood estimation yields sparser SVC models and achieves a smaller information criterion than classical maximum likelihood estimation. In a cross-validation study applied on the real data, we show that our proposed penalized maximum likelihood estimation consistently yields the sparsest SVC models while achieving similar predictive performance compared to other SVC modeling methodologies. Keywords: Adaptive LASSO; Bayesian optimization; coordinate descent algorithm; model- based optimization; penalized maximum likelihood estimation; spatial statistics
	BibTeX: @ARTICLE{Damb:Sigr:Furr:22, AUTHOR = {Jakob A. Dambon and Fabio Sigrist and Reinhard Furrer}, TITLE = {Joint variable selection of both fixed and random effects for Gaussian process-based spatially varying coefficient models}, JOURNAL = {TGIS}, FJOURNAL = {International Journal of Geographical Information Science}, YEAR = {2022}, DOI = {10.1080/13658816.2022.2097684}, VOLUME = {36}, NUMBER = {12}, PAGES = {2525-2548}, ARXIV = {https://arxiv.org/abs/2101.01932}, FUNDING = {Innosuisse 28408.1 PFES-ES, SNSF-175529}, DISPLAY = {Dambon J. A., Sigrist, F. and Furrer, R. (2022). Joint variable selection of both fixed and random effects for Gaussian process-based spatially varying coefficient models. International Journal of Geographical Information Science, 36(12), 2525–2548.}, }
	Delucchi, M., Spinner, G. R., Scutari, M., Bijlenga, P., Morel, S., Friedrich, C. M., Furrer, R. and Hirsch, S. (2022). Bayesian network analysis reveals the interplay of intracranial aneurysm rupture risk factors. Computers in Biology and Medicine, 147, 105740. [Abstract] [BibTeX]
	Abstract: Clinical decision making regarding the treatment of unruptured intracranial aneurysms (IA) benefits from a better understanding of the interplay of IA rupture risk factors. Probabilistic graphical models can capture and graphically display potentially causal relationships in a mechanistic model. In this study, Bayesian networks (BN) were used to estimate IA rupture risk factors influences. From 1248 IA patient records, a retrospective, single-cohort, patient-level data set with 9 phenotypic rupture risk factors (n=790 complete entries) was extracted. Prior knowledge together with score-based structure learning algorithms estimated rupture risk factor interactions. Two approaches, discrete and mixed-data additive BN, were implemented and compared. The corresponding graphs were learned using non-parametric bootstrapping and Markov chain Monte Carlo, respectively. The BN models were compared to standard descriptive and regression analysis methods. Correlation and regression analyses showed significant associations between IA rupture status and patient’s sex, familial history of IA, age at IA diagnosis, IA location, IA size and IA multiplicity. BN models confirmed the findings from standard analysis methods. More precisely, they directly associated IA rupture with familial history of IA, IA size and IA location in a discrete framework. Additive model formulation, enabling mixed-data, found that IA rupture was directly influenced by patient age at diagnosis besides additional mutual influences of the risk factors. This study establishes a data-driven methodology for mechanistic disease modelling of IA rupture and shows the potential to direct clinical decision-making in IA treatment, allowing personalised prediction. Keywords: Intracranial aneurysm, Bayesian network, Probabilistic graphical model
	BibTeX: @ARTICLE{Delu:etal:Furr:Hirs:22, AUTHOR = {Matteo Delucchi and Georg R. Spinner and Marco Scutari and Philippe Bijlenga and Sandrine Morel and Christoph M. Friedrich and Reinhard Furrer and Sven Hirsch}, TITLE = {Bayesian network analysis reveals the interplay of intracranial aneurysm rupture risk factors}, JOURNAL = {Comput. Biol. Med.}, FJOURNAL = {Computers in Biology and Medicine}, YEAR = {2022}, DOI = {10.1016/j.compbiomed.2022.105740}, VOLUME = {147}, PAGES = {105740}, FUNDING = {div}, DISPLAY = {Delucchi, M., Spinner, G. R., Scutari, M., Bijlenga, P., Morel, S., Friedrich, C. M., Furrer, R. and Hirsch, S. (2022). Bayesian network analysis reveals the interplay of intracranial aneurysm rupture risk factors. Computers in Biology and Medicine, 147, 105740.}, }
	Blasi, F., Caamaño-Carrillo, C., Bevilacqua, M. and Furrer, R. (2022). A selective view of climatological data and likelihood estimation. Spatial Statistics, 50, 100596. [Abstract] [BibTeX] [Git Repo]
	Abstract: This article gives a narrative overview of what constitutes climatological data and their typical features, with a focus on aspects relevant to statistical modeling. We restrict the discussion to univariate spatial fields and focus on maximum likelihood estimation. To address the problem of enormous datasets, we study three common approximation schemes: tapering, direct misspecification, and composite likelihood for Gaussian and non-Gaussian distributions. We focus particularly on the so-called 'sinh-arcsinh distribution', obtained through a specific transformation of the Gaussian distribution. Because it has flexible marginal distributions - possibly skewed and/or heavy-tailed -it has a wide range of applications. One appealing property of the transformation involved is the existence of an explicit inverse transformation that makes likelihood-based methods straightforward. We describe a simulation study illustrating the effects of the different approximation schemes. To the best of our knowledge, a direct comparison of tapering, direct misspecification, and composite likelihood has never been made previously, and we show that direct misspecification is inferior. In some metrics, composite likelihood has a minor advantage over tapering. We use the estimation approaches to model a high-resolution global climate change field. All simulation code is available as a docker container and is thus fully reproducible. Additionally, the present article describes where and how to get various climate datasets. Keywords: tapering; composite likelihood; sinh-arcsinh distribution; CMIP6 data; random field; spatial process
	BibTeX: @ARTICLE{Blas:etal:Furr:22, AUTHOR = {Federico Blasi and Christian Caamaño-Carrillo and Moreno Bevilacqua and Reinhard Furrer}, TITLE = {A selective view of climatological data and likelihood estimation}, JOURNAL = {Spat. Stat.}, FJOURNAL = {Spatial Statistics}, YEAR = {2022}, DOI = {10.1016/j.spasta.2022.100596}, VOLUME = {50}, PAGES = {100596}, FUNDING = {SNSF-17552 and more}, DISPLAY = {Blasi, F., Caamaño-Carrillo, C., Bevilacqua, M. and Furrer, R. (2022). A selective view of climatological data and likelihood estimation. Spatial Statistics, 50, 100596.}, }
	Ingelfinger, F., Gerdes, L. A., Kavaka, V. et al. (2022). Twin study reveals non-heritable immune perturbations in multiple sclerosis. Nature, 603, 152–158. [Abstract] [BibTeX]
	Abstract: Multiple sclerosis (MS) is a chronic inflammatory disorder of the central nervous system underpinned by partially understood genetic risk factors and environmental triggers and their undefined interactions1,2. Here we investigated the peripheral immune signatures of 61 monozygotic twin pairs discordant for MS to dissect the influence of genetic predisposition and environmental factors. Using complementary multimodal high-throughput and high-dimensional single-cell technologies in conjunction with data-driven computational tools, we identified an inflammatory shift in a monocyte cluster of twins with MS, coupled with the emergence of a population of IL-2 hyper-responsive transitional naive helper T cells as MS-related immune alterations. By integrating data on the immune profiles of healthy monozygotic and dizygotic twin pairs, we estimated the variance in CD25 expression by helper T cells displaying a naive phenotype to be largely driven by genetic and shared early environmental influences. Nonetheless, the expanding helper T cells of twins with MS, which were also elevated in non-twin patients with MS, emerged independent of the individual genetic makeup. These cells expressed central nervous system-homing receptors, exhibited a dysregulated CD25–IL-2 axis, and their proliferative capacity positively correlated with MS severity. Together, our matched-pair analysis of the extended twin approach allowed us to discern genetically and environmentally determined features of an MS-associated immune signature. Keywords:
	BibTeX: @ARTICLE{Inge:Gerd:etal:22, AUTHOR = {Florian Ingelfinger and Lisa Ann Gerdes and Vladyslav Kavaka and Sinduya Krishnarajah and Ekaterina Friebel and Edoardo Galli and Pascale Zwicky and Reinhard Furrer and Christian Peukert and Charles-Antoine Dutertre and Klara Magdalena Eglseer and Florent Ginhoux and Andrea Flierl-Hecht and Tania Kümpfel and Donatella De Feo and Bettina Schreiner and Sarah Mundt and Martin Kerschensteiner and Reinhard Hohlfeld and Eduardo Beltrán and Burkhard Becher}, TITLE = {Twin study reveals non-heritable immune perturbations in multiple sclerosis}, JOURNAL = {Nature}, FJOURNAL = {Nature}, YEAR = {2022}, DOI = {10.1038/s41586-022-04419-4}, VOLUME = {603}, PAGES = {152--158}, ARXIV = {https://arxiv.org/abs/2007.14684}, FUNDING = {}, DISPLAY = {Ingelfinger, F., Gerdes, L. A., Kavaka, V. et al. (2022) Twin study reveals non-heritable immune perturbations in multiple sclerosis. Nature 603, 152–158.}, }
	Gupta, A., Furrer, R. and Petchey, O. L. (2022). Simultaneously estimating food web connectance and structure with uncertainty. Ecology and Evolution, 12, e8643. [Abstract] [BibTeX]
	Abstract: Food web models explain and predict the trophic interactions in a food web, and they can infer missing interactions among the organisms. The allometric diet breadth model (ADBM) is a food web model based on the foraging theory. In the ADBM, the foraging parameters are allometrically scaled to body sizes of predators and prey. In Petchey et al. (Proceedings of the National Academy of Sciences, 2008; 105: 4191), the parameterization of the ADBM had two limitations: (a) the model parameters were point estimates and (b) food web connectance was not estimated. The novelty of our current approach is: (a) We consider multiple predictions from the ADBM by parameterizing it with approximate Bayesian computation, to estimate parameter distributions and not point estimates. (b) Connectance emerges from the parameterization, by measuring model fit using the true skill statistic, which takes into account prediction of both the presences and absences of links. We fit the ADBM using approximate Bayesian computation to 12 observed food webs from a wide variety of ecosystems. Estimated connectance was consistently greater than previously found. In some of the food webs, considerable variation in estimated parameter distributions occurred and resulted in considerable variation (i.e., uncertainty) in predicted food web structure. These results lend weight to the possibility that the observed food web data is missing some trophic links that do actually occur. It also seems likely that the ADBM likely predicts some links that do not exist. The latter could be addressed by accounting in the ADBM for additional traits other than body size. Further work could also address the significance of uncertainty in parameter estimates for predicted food web responses to environmental change. Keywords: ABC, ADBM, connectance, food web, true skill statistic, uncertainty
	BibTeX: @ARTICLE{Gupt:Furr:Petc:22, AUTHOR = {Gupta, A. and Furrer, R. and Petchey, O. L.}, TITLE = {Simultaneously estimating food web connectance and structure with uncertainty}, JOURNAL = {Ecology and Evolution}, FJOURNAL = {Ecology and Evolution}, YEAR = {2022}, DOI = {10.1002/ece3.8643}, VOLUME = {12}, PAGES = {e8643}, ARXIV = {https://arxiv.org/abs/2007.14684}, FUNDING = {URPP GCB}, DISPLAY = {Gupta, A., Furrer, R., and Petchey, O. L. (2022). Simultaneously estimating food web connectance and structure with uncertainty. Ecology and Evolution, 12, e8643.}, }

2021

	Flury, R. C. and Furrer, R. (2021). Discussion on Competition for Spatial Statistics for Large Datasets Title Case. Journal of Agricultural, Biological, and Environmental Statistics, 26, 599–603. [Abstract] [BibTeX]
	Abstract: We discuss the experiences and results of the AppStatUZH team’s participation in the comprehensive and unbiased comparison of different spatial approximations conducted in the Competition for Spatial Statistics for Large Datasets. In each of the different sub-competitions, we estimated parameters of the covariance model based on a likelihood function and predicted missing observations with simple kriging. We approximated the covariance model either with covariance tapering or a compactly supported Wendland covariance function.
	BibTeX: @ARTICLE{Flur:Furr:21, AUTHOR = {Flury, R. C. and Furrer, R.}, TITLE = {Discussion on Competition for Spatial Statistics for Large Datasets}, JOURNAL = {J. Agric. Biol. Environ. Stat.}, FJOURNAL = {Journal of Agricultural, Biological, and Environmental Statistics}, YEAR = {2021}, DOI = {10.1007/s13253-021-00461-3}, VOLUME = {26}, PAGES = {599--603}, ARXIV = {https://arxiv.org/abs/2106.10462}, FUNDING = {SNSF-175529}, DISPLAY = {Flury, R. C. and Furrer, R. (2021). Discussion on Competition for Spatial Statistics for Large Datasets Title Case. Journal of Agricultural, Biological, and Environmental Statistics, 26, 599–603.}, }
	Guillén Escribà, C., Schneider, F., Schmid, B., Tedder, A., Morsdorf, F., Furrer, R., Hueni, A., Niklaus, P., and Schaepman, M. E. (2021). Remotely sensed between-individual functional trait variation in a temperate forest. Ecology and Evolution, 11(16), 310834–10867. [Abstract] [BibTeX]
	Abstract: 1. Trait-based ecology holds the promise to explain how plant communities work, for example, how functional diversity may support community productivity. However, so far it has been difficult to combine field-based approaches assessing traits at the level of plant individuals with limited spatial coverage and approaches using remote sensing (RS) with complete spatial coverage but assessing traits at the level of vegetation pixels rather than individuals. By delineating all individual-tree crowns within a temperate forest site and then assigning RS-derived trait measures to these trees, we combine the two approaches, allowing us to use general linear models to estimate the influence of taxonomic or environmental variation on between- and within-species variation across contiguous space. 2. We used airborne imaging spectroscopy and laser scanning to collect individual-tree RS data from a mixed conifer-angiosperm forest on a mountain slope extending over 5.5 ha and covering large environmental gradients in elevation as well as light and soil conditions. We derived three biochemical (leaf chlorophyll, carotenoids, and water content) and three architectural traits (plant area index, foliage-height diversity, and canopy height), which had previously been used to characterize plant function, from the RS data. We then quantified the contributions of taxonomic and environmental variation and their interaction to trait variation and partitioned the remaining within-species trait variation into smaller-scale spatial and residual variation. We also investigated the correlation between functional trait and phylogenetic distances at the between-species level. The forest consisted of 13 tree species of which eight occurred in sufficient abundance for quantitative analysis. 3. On average, taxonomic variation between species accounted for more than 15% of trait variation in biochemical traits but only around 5% (still highly significant) in architectural traits. Biochemical trait distances among species also showed a stronger correlation with phylogenetic distances than did architectural trait distances. Light and soil conditions together with elevation explained slightly more variation than taxonomy across all traits, but in particular increased plant area index (light) and reduced canopy height (elevation). Except for foliage-height diversity, all traits were affected by significant interactions between taxonomic and environmental variation, the different responses of the eight species to the within-site environmental gradients potentially contributing to the coexistence of the eight abundant species. 4. We conclude that with high-resolution RS data it is possible to delineate individual-tree crowns within a forest and thus assess functional traits derived from RS data at individual level. With this precondition fulfilled, it is then possible to apply tools commonly used in field-based trait ecology to partition trait variation among individuals into taxonomic and potentially even genetic variation, environmental variation, and interactions between the two. The method proposed here presents a promising way of assessing individual-based trait information with complete spatial coverage and thus allowing analysis of functional diversity at different scales. This information can help to better understand processes shaping community structure, productivity, and stability of forests.
	BibTeX: @ARTICLE{Furr::21, AUTHOR = {Guillén Escribà, Carla and Schneider, Fabian and Schmid, Bernhard and Morsdorf, Felix and Tedder, Andrew and Furrer, Reinhard and Niklaus, Pascal and Hueni, Andreas and Schaepman, Michael}, TITLE = {Remotely sensed between-individual functional trait variation in a temperate forest}, JOURNAL = {Ecol. Evol.}, FJOURNAL = {Ecology and Evolution}, YEAR = {2021}, DOI = {10.1002/ece3.7758}, VOLUME = {11}, NUMBER = {16}, PAGES = {10834--10867}, FUNDING = {URPP GCB and more}, DISPLAY = {Guillén Escribà, C., Schneider, F., Schmid, B., Morsdorf, F., Tedder, A., Furrer, R., Niklaus, P., Hueni, A., and Schaepman, M. E., (2021). Remotely sensed between-individual functional trait variation in a temperate forest. Ecology and Evolution, 11(16), 310834–10867.}, }
	Paternoster, G., Boo, G.⁺, Flury, R.⁺, Raimkulov, K. M., Minbaeva, G., Usubalieva, J., Bondarenko, M., Müllhaupt, B., Deplazes, P., Furrer, R.^\| and Torgerson, P. R.^\| (2021). Association between environmental and climatic risk factors and the spatial distribution of cystic and alveolar echinococcosis in Kyrgyzstan. PLOS Neglected Tropical Diseases, 15(6), e0009498. [Abstract] [BibTeX]
	Abstract: Background: Cystic and alveolar echinococcosis (CE and AE) are neglected tropical diseases caused by Echinococcus granulosus sensu lato and E. multilocularis, and are emerging zoonoses in Kyrgyzstan. In this country, the spatial distribution of CE and AE surgical incidence in 2014-2016 showed marked heterogeneity across communities, suggesting the presence of ecological determinants underlying CE and AE distributions. Methodology/Principal findings: For this reason, in this study we assessed potential associations between community-level confirmed primary CE (no.=2359) or AE (no.=546) cases in 2014-2016 in Kyrgyzstan and environmental and climatic variables derived from satellite-remote sensing datasets using conditional autoregressive models. We also mapped CE and AE relative risk. The number of AE cases was negatively associated with 10-year lag mean annual temperature. Although this time lag should not be considered as an exact measurement but with associated uncertainty, it is consistent with the estimated 10–15-year latency following AE infection. No associations were detected for CE. We also identified several communities at risk for CE or AE where no disease cases were reported in the study period. Conclusions/Significance: Our findings support the hypothesis that CE is linked to an anthropogenic cycle and is less affected by environmental risk factors compared to AE, which is believed to result from spillover from a wild life cycle. As CE was not affected by factors we investigated, hence control should not have a geographical focus. In contrast, AE risk areas identified in this study without reported AE cases should be targeted for active disease surveillance in humans. This active surveillance would confirm or exclude AE transmission which might not be reported with the present passive surveillance system. These areas should also be targeted for ecological investigations in the animal hosts.
	BibTeX: @ARTICLE{Pate:etal:21, AUTHOR = {Giulia Paternoster and Gianluca Boo and Roman Flury and Kursanbek M. Raimkulov and Gulnara Minbaeva and Jumagul Usubalieva and Maksym Bondarenko and Beat Müllhaupt and Peter Deplazes and Reinhard Furrer and Paul R. Torgerson}, TITLE = {Association between environmental and climatic risk factors and the spatial distribution of cystic and alveolar echinococcosis in Kyrgyzstan}, JOURNAL = {PLoS Negl. Trop. Dis.}, FJOURNAL = {PLoS Neglected Tropical Diseases}, YEAR = {2021}, DOI = {10.1371/journal.pntd.0009498}, VOLUME = {15}, NUMBER = {6}, PAGES = {e0009498}, FUNDING = {SNSF-175529, and more}, DISPLAY = {Paternoster, G., Boo, G., Flury, R., Raimkulov, K. M., Minbaeva, G., Usubalieva, J., Bondarenko, M., Müllhaupt, B., Deplazes, P., Furrer, R. and Torgerson, P. R. (2021). Association between environmental and climatic risk factors and the spatial distribution of cystic and alveolar echinococcosis in Kyrgyzstan. PLOS Neglected Tropical Diseases, 15(6), e0009498.}, }
	Rocchini, D., Thouverai, E, Marcantonio, M, et al. (2021). rasterdiv - An Information Theory tailored R package for measuring ecosystem heterogeneity from space: To the origin and back. Methods in Ecology and Evolution, 12(6), 1093–1102. [Abstract] [BibTeX]
	Abstract: Ecosystem heterogeneity has been widely recognized as a key ecological indicator of several ecological functions, diversity patterns and change, metapopulation dynamics, population connectivity or gene flow. In this paper, we present a new R package—rasterdiv—to calculate heterogeneity indices based on remotely sensed data. We also provide an ecological application at the landscape scale and demonstrate its power in revealing potentially hidden heterogeneity patterns. The rasterdiv package allows calculating multiple indices, robustly rooted in Information Theory, and based on reproducible open-source algorithms. Keywords: biodiversity, ecological informatics, modelling, remote sensing, satellite imagery
	BibTeX: @ARTICLE{Rocc:etal:MEE, AUTHOR = {Rocchini, Duccio and Thouverai, Elisa and Marcantonio, Matteo and Iannacito, Martina and Da Re, Daniele and Torresani, Michele and Bacaro, Giovanni and Bazzichetto, Manuele and Bernardi, Alessandra and Foody, Giles M. and Furrer, Reinhard and Kleijn, David and Larsen, Stefano and Lenoir, Jonathan and Malavasi, Marco and Marchetto, Elisa and Messori, Filippo and Montaghi, Alessandro and Moudrý, Vítězslav and Naimi, Babak and Ricotta, Carlo and Rossini, Micol and Santi, Francesco and Santos, Maria J. and Schaepman, Michael E. and Schneider, Fabian D. and Schuh, Leila and Silvestri, Sonia and Ŝímová, Petra and Skidmore, Andrew K. and Tattoni, Clara and Tordoni, Enrico and Vicario, Saverio and Zannini, Piero and Wegmann, Martin}, TITLE = {rasterdiv - an Information Theory tailored R package for measuring ecosystem heterogeneity from space: to the origin and back}, JOURNAL = {Methods Ecol. Evol.}, FJOURNAL = {Methods in Ecology and Evolution}, YEAR = {2021}, DOI = {10.1111/2041-210X.13583}, VOLUME = {12}, NUMBER = {6}, PAGES = {1093--1102}, FUNDING = {GCB and other}, DISPLAY = {Rocchini, D., Thouverai, E, Marcantonio, M, et al. (2021). rasterdiv - An Information Theory tailored R package for measuring ecosystem heterogeneity from space: To the origin and back. Methods in Ecology and Evolution, 12(6), 1093–1102.}, }
	Wang, C. and Furrer, R. (2021). Combining Heterogeneous Spatial Datasets with Process-based Spatial Fusion Models: A Unifying Framework. Computational Statistics & Data Analysis, 161, 107240. [Abstract] [BibTeX]
	Abstract:In modern spatial statistics, the structure of data that is collected has become more heterogeneous. Depending on the type of spatial data, different modeling strategies for spatial data are used. For example, a kriging approach for geostatistical data; a Gaussian Markov random field model for lattice data; or a log Gaussian Cox process for point-pattern data. Despite these different modeling choices, the nature of underlying scientific data-generating (latent) processes is often the same, which can be represented by some continuous spatial surfaces. In this paper, we introduce a unifying framework for process-based multivariate spatial fusion models. The framework can jointly analyze all three aforementioned types of spatial data (or any combinations thereof). Moreover, the framework accommodates different conditional distributions for geostatistical and lattice data. We show that some established approaches, such as linear models of coregionalization, can be viewed as special cases of our proposed framework. We offer flexible and scalable implementations in R using Stan and INLA. Simulation studies confirm that the predictive performance of latent processes improves as we move from univariate spatial models to multivariate spatial fusion models. The introduced framework is illustrated using a cross-sectional study linked with a national cohort dataset in Switzerland, we examine differences in underlying spatial risk patterns between respiratory disease and lung cancer. Keywords: Bayesian methods, Change of support problem, Data fusion, Gaussian process
	BibTeX: @ARTICLE{Wang:Furr:21, AUTHOR = {Craig Wang and Reinhard Furrer}, TITLE = {Combining Heterogeneous Spatial Datasets with Process-based Spatial Fusion Models: A Unifying Framework}, JOURNAL = {Comput. Statist. Data Anal.}, FJOURNAL = {Computational Statistics \& Data Analysis}, YEAR = {2021}, DOI = {10.1016/j.csda.2021.107240}, VOLUME = {161}, PAGES = {107240}, FUNDING = {SNSF 175529, 3347CO-108806, 33CS30-134273 and 33CS30-148415. SNC}, ARXIV = {https://arxiv.org/abs/1906.00364}, DISPLAY = {Wang, C. and Furrer, R. (2021). Combining Heterogeneous Spatial Datasets with Process-based Spatial Fusion Models: A Unifying Framework. Computational Statistics & Data Analysis, 161, 107240. }, }
	Flury, R., Gerber, F., Schmid, B. and Furrer, R. (2021). Identification of Dominant Features in Spatial Data. Spatial Statistics, 41, 100483. [Abstract] [BibTeX] [Data]
	Abstract: Dominant features of spatial data are connected structures or patterns that emerge from location-based variation and manifest at specific scales or resolutions. To identify dominant features, we propose a sequential application of multiresolution decomposition and variogram function estimation. Multiresolution decomposition separates data into additive components, and in this way enables the recognition of their dominant features. A dedicated multiresolution decomposition method is developed for arbitrary gridded spatial data, where the underlying model includes a precision and spatial-weight matrix to capture spatial correlation. The data are separated into their components by smoothing on different scales, such that larger scales have longer spatial correlation ranges. Moreover, our model can handle missing values, which is often useful in applications. Variogram function estimation can be used to describe properties in spatial data. Such functions are therefore estimated for each component to determine its effective range, which assesses the width-extent of the dominant feature. Finally, Bayesian analysis enables the inference of identified dominant features and to judge whether these are credibly different. The efficient implementation of the method relies mainly on a sparse-matrix data structure and algorithms. By applying the method to simulated data we demonstrate its applicability and theoretical soundness. In disciplines that use spatial data, this method can lead to new insights, as we exemplify by identifying the dominant features in a forest dataset. In that application, the width-extents of the dominant features have an ecological interpretation, namely the species interaction range, and their estimates support the derivation of ecosystem properties such as biodiversity indices. Keywords: Scale-space analysis; Lattice data; Gaussian Markov random field; Maximum norm; Moving-window size.
	BibTeX: @ARTICLE{Flur:Gerb:Schm:Furr:21, AUTHOR = {Roman Flury and Florian Gerber and Bernhard Schmid and Reinhard Furrer}, TITLE = {Identification of dominant features in spatial data}, JOURNAL = {Spat. Stat.}, FJOURNAL = {Spatial Statistics}, YEAR = {2021}, DOI = {10.1016/j.spasta.2020.100483}, VOLUME = {41}, PAGES = {100483}, ARXIV = {https://arxiv.org/abs/2006.07183}, FUNDING = {SNSF 175529, P400P2_186680, P2ZHP2_174828 and URPP GCB}, DISPLAY = {Flury, R., Gerber, F., Schmid, B. and Furrer, R. (2021). Identification of Dominant Features in Spatial Data. Spatial Statistics, 41, 100483.}, }
	Dambon, J. A., Sigrist, F., and Furrer, R. (2021). Maximum likelihood estimation of spatially varying coefficient models for large data with an application to real estate price prediction. Spatial Statistics, 41, 100470. [Abstract] [BibTeX]
	Abstract: In regression models for spatial data, it is often assumed that the marginal effects of covariates on the response are constant over space. In practice, this assumption might often be questionable. In this article, we show how a Gaussian process-based spatially varying coefficient (SVC) model can be estimated using maximum likelihood estimation (MLE). In addition, we present an approach that scales to large data by applying covariance tapering. We compare our methodology to existing methods such as a Bayesian approach using the stochastic partial differential equation (SPDE) link, geographically weighted regression (GWR), and eigenvector spatial filtering (ESF) in both a simulation study and an application where the goal is to predict prices of real estate apartments in Switzerland. The results from both the simulation study and application show that the MLE approach results in increased predictive accuracy and more precise estimates. Since we use a model-based approach, we can also provide predictive variances. In contrast to existing model-based approaches, our method scales better to data where both the number of spatial points is large and the number of spatially varying covariates is moderately-sized, e.g., above ten. Keywords: Spatial statistics; Gaussian process; Covariance tapering; Likelihood regularization; Real estate mass appraisal
	BibTeX: @ARTICLE{Damb:Sigr:Furr:21, AUTHOR = {Dambon, J. A. and Sigrist, F. and Furrer, R.}, TITLE = {Maximum likelihood estimation of spatially varying coefficient models for large data with an application to real estate price prediction}, JOURNAL = {Spat. Stat.}, FJOURNAL = {Spatial Statistics}, YEAR = {2020}, DOI = {10.1016/j.spasta.2020.100470}, VOLUME = {41}, PAGES = {100470}, ARXIV = {https://arxiv.org/abs/2001.08089}, FUNDING = {SNSF 175529, Innosuisse 28408.1 PFES-ES}, DISPLAY = {Dambon, J. A., Sigrist, F., and Furrer, R. (2021). Maximum likelihood estimation of spatially varying coefficient models for large data with an application to real estate price prediction. Spatial Statistics, 41, 100470}, }
	Rocchini, D. et al. (2021). From zero to infinity: Minimum to maximum diversity of the planet by spatio-parametric Rao’s quadratic entropy. Global Ecology and Biogeography, 30(5), 1153–1162. [Abstract] [BibTeX]
	Abstract: Aim: The majority of work done to gather information on Earth diversity has been carried out using in-situ data, with known issues related to epistemology (e.g., species determination and taxonomy), spatial uncertainty, logistics (time and costs), among others. An alternative way to gather information about spatial ecosystem variability is the use of satellite remote sensing. It works as a powerful tool for attaining rapid and standardized information. Several metrics used to calculate remotely sensed diversity of ecosystems are based on Shannon’s information theory, namely on the differences in relative abundance of pixel reflectances in a certain area. Additional metrics like the Rao’s quadratic entropy allow the use of spectral distance beside abundance, but they are point descriptors of diversity, that is they can account onlyfor a part of the whole diversity continuum. The aim of this paper is thus to generalize the Rao’s quadratic entropy by proposing its parameterization for the first time. Innovation: The parametric Rao’s quadratic entropy, coded in R, (a) allows the representation of the whole continuum of potential diversity indices in one formula, and (b) starting from the Rao’s quadratic entropy, allows the explicit use of distances among pixel reflectance values, together with relative abundances. Main conclusions: The proposed unifying measure is an integration between abun- dance- and distance-based algorithms to map the continuum of diversity given a satellite image at any spatial scale. Being part of the rasterdiv R package, the proposed method is expected to ensure high robustness and reproducibility. Keywords: biodiversity, ecological informatics, modelling, remote sensing, satellite imagery
	BibTeX: @ARTICLE{Rocc:etal:GEB, AUTHOR = {Duccio Rocchini and Matteo Marcantonio and Daniele Da Re and Giovanni Bacaro and Enrico Feoli and Giles M. Foody and Reinhard Furrer and Ryan J. Harrigan and David Kleijn and Martina Iannacito and Jonathan Lenoir and Meixi Lin and Marco Malavasi and Elisa Marchetto and Rachel S. Meyer and Vítězslav Moudrý and Davnah Payne and Fabian D. Schneider and Petra Šímová and Andrew H. Thornhill and Elisa Thouverai and Saverio Vicario and Robert K. Wayne and Carlo Ricotta}, TITLE = {From zero to infinity: Minimum to maximum diversity of the planet by spatio-parametric {Rao's} quadratic entropy}, JOURNAL = {Glob. Ecol. Biogeogr.}, FJOURNAL = {Global Ecology and Biogeography}, YEAR = {2021}, DOI = {10.1111/geb.13270}, BIORXIV = {10.1101/2021.01.23.427872v1}, VOLUME = {30}, NUMBER = {5}, PAGES = {1153--1162}, FUNDING = {SNSF 175529 and more}, DISPLAY = {Rocchini, D. et al. (2021). From zero to infinity: Minimum to maximum diversity of the planet by spatio-parametric Rao’s quadratic entropy. Global Ecology and Biogeography, 30(5), 1153–1162.}, }
	Folly, C. L., Konstatinoudis, G., Mazzei-Abba, A., Kreis, C., Bucher, B., Furrer, R. and Spycher, B. D. (2021). Bayesian spatial modelling of terrestrial radiation in Switzerland. Journal of Environmental Radioactivity, 233, 106571. [Abstract] [BibTeX]
	Abstract: The geographic variation of terrestrial radiation can be exploited in epidemiological studies of the health effects of protracted low-dose exposure. Various methods have been applied to derive maps of this variation. We aimed to construct a map of terrestrial radiation for Switzerland. We used airborne gamma-spectrometry measurements to model the ambient dose rates from terrestrial radiation through a Bayesian mixed-effects model and conducted inference using Integrated Nested Laplace Approximation (INLA). We predicted higher levels of ambient dose rates in the alpine regions and Ticino compared with the western and northern parts of Switzerland. We provide a map that can be used for exposure assessment in epidemiological studies and as a baseline map for assessing potential contamination. Keywords: Gaussian Markov random fields, Natural background radiation, Spatial statistics, Stochastic partial differential equation, Low-dose ionising radiation
	BibTeX: @ARTICLE{Foll:etal:21, AUTHOR = {Christophe L. Folly and Garyfallos Konstatinoudis and Antonella Mazzei-Abba and Christian Kreis and Benno Bucher and Reinhard Furrer and Ben D. Spycher}, TITLE = {Bayesian spatial modelling of terrestrial radiation in {Switzerland}}, JOURNAL = {J. Environ. Radioact.}, FJOURNAL = {Journal of Environmental Radioactivity}, YEAR = {2021}, DOI = {10.1016/j.jenvrad.2021.106571}, VOLUME = {233}, NUMBER = {July}, PAGES = {106571}, ARXIV = {https://arxiv.org/abs/2010.00534}, FUNDING = {div}, DISPLAY = {Folly, C. L., Konstatinoudis, G., Mazzei-Abba, A., Kreis, C., Bucher, B., Furrer, R. and Spycher, B. D. (2021). Bayesian spatial modelling of terrestrial radiation in Switzerland. Journal of Environmental Radioactivity, 233, 106571.}, }
	Porcu, E., Furrer, R., and Nychka, D. (2021). 30 Years of Space-time covariance functions. Wiley interdisciplinary reviews. Computational statistics, 13:e1512, 1–24. [Abstract] [BibTeX]
	Abstract: In this article we provide a comprehensive review of space-time covariance functions. As for the spatial domain, we focus on either the $d$-dimensional Euclidian space or on the unit d-dimensional sphere. We start by providing background information about (spatial) covariance functions and their properties along with different types of covariance functions. While we focus primarily on Gaussian processes, many of the results are independent of the underlying distribution, as the covariance only depends on second-moment relationships. We discuss properties of space-time covariance functions along with the relevant results associated with spectral representations. Special attention is given to the Gneiting class of covariance functions, which has been especially popular in space-time geostatistical modeling. We then discuss some techniques that are useful for constructing new classes of space-time covariance functions. Separate treatment is reserved for spectral models, as well as to what are termed models with special features. We also discuss the problem of estimation of parametric classes of space-time covariance functions. An outlook concludes the paper. Keywords: Dynamical models, Gneiting functions, scale mixture, spectral representation, great circle distance.
	BibTeX: @ARTICLE{Porc:Furr:Nych:21, AUTHOR = {Emilio Porcu and Reinhard Furrer and Douglas Nychka}, TITLE = {30 Years of Space-time covariance functions}, JOURNAL = {Wiley Interdiscip. Rev. Comput. Stat.}, FJOURNAL = {Wiley interdisciplinary reviews. Computational statistics}, YEAR = {2020}, DOI = {10.1002/wics.1512}, VOLUME = {13:e1512}, PAGES = {1--24}, FUNDING = {SNSF-175529 and more}, DISPLAY = {Porcu, E., Furrer, R., and Nychka, D. (2021). 30 Years of Space-time covariance functions. Wiley interdisciplinary reviews. Computational statistics, 13:e1512, 1–24.}, }

2020

	Schuh, L., Furrer, F., Schaepman, M., Santos, M. J. and de Jong, R. (2020). Advancing Texture Metrics to Model Landscape Heterogeneity. In: IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, Waikoloa, HI, USA, pp. 2735-2738. [Abstract] [BibTeX]
	Abstract: We advance methods to study landscape heterogeneity and assess the suitability of these methods to detect boundary regions between land cover types. We employ 2nd-order texture metrics on continuous and on discrete vegetation data in North Eurasia and on a smaller region therein. Furthermore, we advance 2nd-order texture metrics to incorporate spatial scales in novel ways. The metrics entropy, contrast, and homogeneity are found to detect boundary regions well on discrete data in the smaller study area, but create fuzzy results on continuous data and when models are run for the whole of northern Eurasia. The scales we consider affect the size of the boundary regions, but also the metric values. The results elucidate the need for aligned scale determination and data restriction procedures. Our approach offers new opportunities to model landscape heterogeneity across scales. Index Terms: Between type heterogeneity, within type heterogeneity, 2nd-order texture metrics, entropy, contrast, homogeneity, boundary regions, scale.
	BibTeX: @INPROCEEDINGS{Schu:etal:20, AUTHOR = {Leila Schuh and Reinhard Furrer and Michael Schaepman and Maria J. Santos and Rogier de Jong}, BOOKTITLE = {IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium}, TITLE = {Advancing Texture Metrics to Model Landscape Heterogeneity}, YEAR = {2020}, DOI = {10.1109/IGARSS39084.2020.9323930}, VOLUME = {26 Sept.-2 Oct. 2020}, PAGES = {2735--2738}, FUNDING = {URPP}, DISPLAY = {Schuh, L., Furrer, F., Schaepman, M., Santos, M. J. and de Jong, R. (2020). Advancing Texture Metrics to Model Landscape Heterogeneity. In: IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, Waikoloa, HI, USA, pp. 2735-2738.}, }
	Wang, C., and Furrer, R. (2020). Monte Carlo Permutation Tests for Assessing Spatial Dependence at Different Scales. In: La Rocca M., Liseo B., Salmaso L. (eds) Nonparametric Statistics. ISNPS 2018. Springer Proceedings in Mathematics & Statistics, vol 339. Springer, Cham, pp 503–511. [Abstract] [BibTeX]
	Abstract: Spatially dependent residuals arise as a result of missing or misspecified spatial variables in a model. Such dependence is observed in different areas, including environmental, epidemiological, social, and economic studies. It is crucial to take the dependence into modelling consideration to avoid spurious associations between variables of interest or to avoid wrong inferential conclusions due to underestimated uncertainties. An insight about the scales at which spatial dependence exist can help to comprehend the underlying physical process and to select suitable spatial interpolation methods. In this paper, we propose two Monte Carlo permutation tests to 1) assess the existence of overall spatial dependence and 2) assess spatial dependence at small scales, respectively. A p-value combination method is used to improve statistical power of the tests. We conduct a simulation study to reveal the advantages of our proposed methods in terms of type~I error rate and statistical power. The tests are implemented in an open-source R package `variosig`. Keywords: Spatial data; Combining p-values; Empirical Brown's method; Variogram; Nonparametric
	BibTeX: @INPROCEEDINGS{Wang:Furr:20, AUTHOR = {Craig Wang and Reinhard Furrer}, TITLE = {Monte Carlo Permutation Tests for Assessing Spatial Dependence at Different Scales}, EDITOR = {La Rocca M. and Liseo B. and Salmaso L.}, BOOKTITLE = {Nonparametric Statistics. ISNPS 2018. Springer Proceedings in Mathematics \& Statistics}, PUBLISHER = {Springer}, YEAR = {2020}, DOI = {10.1007/978-3-030-57306-5_45}, VOLUME = {339}, PAGES = {503--511}, FUNDING = {SNSF-175529}, DISPLAY = {Wang, C., and Furrer, R. (2019). Monte Carlo Permutation Tests for Assessing Spatial Dependence at Different Scales. In: La Rocca M., Liseo B., Salmaso L. (eds) Nonparametric Statistics. ISNPS 2018. Springer Proceedings in Mathematics & Statistics, vol 339. Springer, Cham, pp 503–511.}, ShareableLink ={https://rdcu.be/cb1lP}, }
	Carraro, L, Bertuzzo, E., Fronhofer, E. A., Furrer, R., Gounand, I., Rinaldo, A., and Altermatt, F. (2020). Generation and application of river network analogues for use in ecology and evolution. Ecology and Evolution, 10(14), 7537–7550. [Abstract] [BibTeX]
	Abstract: Several key processes in freshwater ecology are governed by the connectivity inherent to dendritic river networks. These have extensively been analyzed from a geomorphological and hydrological viewpoint, yet structures classically used in ecological modeling have been poorly representative of the structure of real river basins, often failing to capture well‐known scaling features of natural rivers. Pioneering work identified optimal channel networks (OCNs) as spanning trees reproducing all scaling features characteristic of natural stream networks worldwide. While OCNs have been used to create landscapes for studies on metapopulations, biodiversity, and epidemiology, their generation has not been generally accessible. Given the increasing interest in dendritic riverine networks by ecologists and evolutionary biologists, we here present a method to generate OCNs and, to facilitate its application, we provide the R‐package OCNet . Owing to the stochastic process generating OCNs, multiple network replicas spanning the same surface can be built; this allows performing computational experiments whose results are irrespective of the particular shape of a single river network. The OCN construct also enables the generation of elevational gradients derived from the optimal network configuration, which can constitute three‐dimensional landscapes for spatial studies in both terrestrial and freshwater realms. Moreover, the package provides functions that aggregate OCNs into an arbitrary number of nodes, calculate several descriptors of river networks, and draw relevant network features. We describe the main functionalities of the package and its integration with other R‐packages commonly used in spatial ecology. Moreover, we exemplify the generation of OCNs and discuss an application to a metapopulation model for an invasive riverine species. In conclusion, OCNet provides a powerful tool to generate realistic river network analogues for various applications. It thereby allows the design of spatially realistic studies in increasingly impacted ecosystems and enhances our knowledge on spatial processes in freshwater ecology in general. Keywords: biodiversity, dispersal, ecological modeling, landscape, metacommunity, optimal channel network, river networks, spanning trees.
	BibTeX: @ARTICLE{Carr:etal:20, AUTHOR = {Luca Carraro, Enrico Bertuzzo, Emanuel A. Fronhofer, Reinhard Furrer, Isabelle Gounand, Andrea Rinaldo, Florian Altermatt}, TITLE = {Generation and application of river network analogues for use in ecology and evolution}, JOURNAL = {Ecol. Evol.}, FJOURNAL = {Ecology and Evolution}, YEAR = {2020}, DOI = {10.1002/ece3.6479}, VOLUME = {10}, NUMBER = {14}, PAGES = {7537--7550}, FUNDING = {URPP, SNF, ...}, DISPLAY = {Carraro, L, Bertuzzo, E., Fronhofer, E. A., Furrer, R., Gounand, I., Rinaldo, A., and Altermatt, F. (2020). Generation and application of river network analogues for use in ecology and evolution. Ecology and Evolution, 10(14), 7537–7550.}, }
	Bachoc, F., Bétancourt, J., Furrer, R., Klein, T. (2020). Asymptotic properties of the maximum likelihood and cross validation estimators for transformed Gaussian processes. Electronic Journal of Statistics, 14(1), 1962–2008. [Abstract] [BibTeX]
	Abstract: The asymptotic analysis of covariance parameter estimation of Gaussian processes has been subject to intensive investigation. However, this asymptotic analysis is very scarce for non-Gaussian processes. In this paper, we study a class of non-Gaussian processes obtained by regular non-linear transformations of Gaussian processes. We provide the increasing-domain asymptotic properties of the (Gaussian) maximum likelihood and cross validation estimators of the covariance parameters of a non-Gaussian process of this class. We show that these estimators are consistent and asymptotically normal, although they are defined as if the process was Gaussian. They do not need to model or estimate the non-linear transformation. Our results can thus be interpreted as a robustness of (Gaussian) maximum likelihood and cross validation towards non-Gaussianity. Our proofs rely on two technical results that are of independent interest for the increasing-domain asymptotic literature of spatial processes. First, we show that, under mild assumptions, coefficients of inverses of large covariance matrices decay at an inverse polynomial rate as a function of the corresponding observation location distances. Second, we provide a general central limit theorem for quadratic forms obtained from transformed Gaussian processes. Finally, our asymptotic results are illustrated by numerical simulations. AMS Classification: 62M30, 62F12. Keywords: covariance parameters, asymptotic normality, consistency, weak dependence, random fields, increasing-domain asymptotics.
	BibTeX: @ARTICLE{Bach:Beta:Furr:Klei:20, AUTHOR = {Fran\c{c}ois Bachoc and Jos\'e Betancourt and Reinhard Furrer and Thierry Klein}, TITLE = {Asymptotic properties of the maximum likelihood and cross validation estimators for transformed {G}aussian processes}, JOURNAL = {Electron. J. Statist.}, FJOURNAL = {Electronic Journal of Statistics}, YEAR = {2020}, DOI = {10.1214/20-EJS1712}, VOLUME = {14}, NUMBER = {1}, PAGES = {1962--2008}, FUNDING = {SNSF-175529 and PEPS from the French Centre national de la recherche scientifique}, DISPLAY = {Bachoc, F., Bétancourt, J., Furrer, R., Klein, T. (2020). Asymptotic properties of the maximum likelihood and cross validation estimators for transformed Gaussian processes. Electronic Journal of Statistics, 14(1), 1962–2008.}, }
	Paternoster, G., Boo, G., Wang, C., Minbaeva, G., Usubalieva, J., Raimkulov, K. M., Zhoroev, A., Abdykerimov, K. K., Kronenberg, P. A., Müllhaupt, B., Furrer, R., Deplazes, P., and Torgerson, P. R. (2020). Epidemic cystic and alveolar echinococcosis in Kyrgyzstan: an analysis of national surveillance data. The Lancet Global Health, 8(4), e603–e611. [Abstract] [BibTeX] [Editorial]
	Summary: Background Human cystic and alveolar echinococcosis are among the priority neglected zoonotic diseases for which WHO advocates control. The incidence of both cystic echinococcosis and alveolar echinococcosis has increased substantially in the past 30 years in Kyrgyzstan. Given the scarcity of adequate data on the local geographical variation of these focal diseases, we aimed to investigate within-country incidence and geographical variation of cystic echinococcosis and alveolar echinococcosis at a high spatial resolution in Kyrgyzstan. Methods We mapped all confirmed surgical cases of cystic echinococcosis and alveolar echinococcosis reported through the national echinococcosis surveillance system in Kyrgyzstan between Jan 1, 2014, and Dec 31, 2016, from nine regional databases. We then estimated crude surgical incidence, standardised incidence, and standardised incidence ratios (SIRs) of primary cases (ie, excluding relapses) based on age and sex at country, region, district, and local community levels. Finally, we tested the SIRs for global and local spatial autocorrelation to identify disease hotspots at the local community level. All incidence estimates were calculated per 100 000 population and averaged across the 3-year study period to obtain annual estimates. Findings The surveillance system reported 2359 primary surgical cases of cystic echinococcosis and 546 primary surgical cases of alveolar echinococcosis. Country-level crude surgical incidence was 13·1 per 100 000 population per year for cystic echinococcosis and 3·02 per 100 000 population per year for alveolar echinococcosis. At the local community level, we found annual crude surgical incidences up to 176 per 100 000 population in Sary-Kamysh (Jalal-Abad region) for cystic echinococcosis and 246 per 100 000 population in Uch-Dobo (Alay district, Osh region) for alveolar echinococcosis. Significant hotspots of cystic echinococcosis were found in four regions: Osh (five local communities in Uzgen district and four in Alay district), Naryn (three local communities in Jumgal district and one in Naryn district), Talas (three local communities in Talas district), and Chuy (one local community in Jayyl district). Significant alveolar echinococcosis hotspots were detected in the Osh region (11 communities in Alay district, including the local community of Sary Mogol, and one in Chong-Alay district) and in the Naryn region (five communities in Jumgal district and three in At-Bashy district), in the southwest and centre of the country. Interpretation Our analyses reveal remarkable within-country variation in the surgical incidence of cystic echinococcosis and alveolar echinococcosis in Kyrgyzstan. These high-resolution maps identify precise locations where interventions and epidemiological research should be targeted to reduce the burden of human cystic echinococcosis and alveolar echinococcosis.
	BibTeX: @ARTICLE{Pate:Boo:Wang:etal:20, AUTHOR = {Giulia Paternoster and Gianluca Boo and Craig Wang and Gulnara Minbaeva and Jumagul Usubalieva and Kursanbek Mamasalievich Raimkulov and Abdykadyr Zhoroev and Kubanychbek Kudaibergenovich Abdykerimov and Philipp Andreas Kronenberg and Beat Müllhaupt and Reinhard Furrer and Peter Deplazes and Paul Robert Torgerson}, TITLE = {Epidemic cystic and alveolar echinococcosis in Kyrgyzstan: an analysis of national surveillance data}, JOURNAL = {}, FJOURNAL = {The Lancet Global Health}, YEAR = {2020}, DOI = {10.1016/S2214-109X(20)30038-3}, VOLUME = {8}, NUMBER = {4}, PAGES = {e603--e611}, FUNDING = {SNF and more}, DISPLAY = {Paternoster, G., Boo, G., Wang, C., Minbaeva, G., Usubalieva, J., Raimkulov, K. M., Zhoroev, A., Abdykerimov, K. K., Kronenberg, P. A., Müllhaupt, B., Furrer, R., Deplazes, P., and Torgerson, P. R. (2020). Epidemic cystic and alveolar echinococcosis in Kyrgyzstan: an analysis of national surveillance data. The Lancet Global Health, 8(4), e603–e611.}, }
	Kratzer, G., Lewis, F. I., Willi, B., Meli, M. L., Boretti, F. S., Hofmann-Lehmann, R., Torgerson, P., Furrer, R. and Hartnack, S. (2020). Bayesian Networks modeling applied to Feline Calicivirus infection among cats in Switzerland. Frontiers in Veterinary Science, 7, 73. [Abstract] [BibTeX] [Supplement (theoretical details)] [R Code]
	Abstract: Bayesian network (BN) modeling is a rich and flexible analytical framework capable of elucidating complex veterinary epidemiological data. It is a graphical modeling technique that enables the visual presentation of multi-dimensional results while retaining statistical rigor in population-level inference. Using previously published case study data about feline calicivirus (FCV) and other respiratory pathogens in cats in Switzerland, a full BN modeling analysis is presented. The analysis shows that reducing the group size and vaccinating animals are the two actionable factors directly associated with FCV status and are primary targets to control FCV infection. The presence of gingivostomatitis and Mycoplasma felis is also associated with FCV status, but signs of upper respiratory tract disease (URTD) are not. FCV data is particularly well-suited to a network modeling approach, as both multiple pathogens and multiple clinical signs per pathogen are involved, along with multiple potentially interrelated risk factors. BN modeling is a holistic approach—all variables of interest may be mutually interdependent—which may help to address issues, such as confounding and collinear factors, as well as to disentangle directly vs. indirectly related variables. We introduce the BN methodology as an alternative to the classical uni- and multivariable regression approaches commonly used for risk factor analyses. We advise and guide researchers about how to use BNs as an exploratory data tool and demonstrate the limitations and practical issues. We present a step-by-step case study using FCV data along with all code necessary to reproduce our analyses in the open-source R environment. We compare and contrast the findings of the current case study using BN modeling with previous results that used classical regression techniques, and we highlight new potential insights. Finally, we discuss advanced methods, such as Bayesian model averaging, a common way of accounting for model uncertainty in a Bayesian network context. Keywords: Feline calicivirus, Reproducible Research, Good Modeling Practice, Graphical Model, Multivariable analysis, Risk factor analysis
	BibTeX: @Proceedings{Krat:etal:20, TITLE = {Bayesian Networks modeling applied to Feline Calicivirus infection among cats in Switzerland}, YEAR = {2020}, AUTHOR = {Gilles Kratzer and Fraser I. Lewis and Barbara Willi and Marina L. Meli and Felicitas S. Boretti and Regina Hofmann-Lehmann and Paul Torgerson Reinhard Furrer and Sonja Hartnack}, JOURNAL = {Front. Vet. Sci.}, FJOURNAL = {Frontiers in Veterinary Science}, VOLUME = {7}, PAGES = {73}, DOI = {10.3389/fvets.2020.00073}, DISPLAY = {Kratzer, G., Lewis, F. I., Willi, B., Meli, M. L., Boretti, F. S., Hofmann-Lehmann, R., Torgerson, P., Furrer, R. and Hartnack, S. (2020). Bayesian Networks modeling applied to Feline Calicivirus infection among cats in Switzerland. Frontiers in Veterinary Science, 7, 73.}, }

2019

	Flury, R. and Furrer, R. (2019). Multiresolution Decomposition of Areal Count Data. In: Cameletti, M., Ippoliti, L., and Pollice, A. (eds.) Proceedings of the GRASPA 2019 Conference, Pescara, 15–16 July 2019, pp. 86–89. [Abstract] [BibTeX]
	Abstract: Multiresolution decomposition is commonly understood as a procedure to capture scaledependent features in random signals. Such methods were first established for image processing and typically rely on raster or regularly gridded data. In this article, we extend a particular multiresolution decomposition procedure to areal count data, i.e. discrete irregularly gridded data. More specifically, we incorporate in a new model concept and distributions from the so-called Besag–York–Mollié model to include a priori demographical knowledge. These adaptions and subsequent changes in the computation schemes are carefully outlined below, whereas the main idea of the original multiresolution decomposition remains. Finally, we show the extension’s feasibility by applying it to oral cavity cancer counts in Germany. Keywords: Spatial scales, Lattice data, Intrinsic GMRF, Besag–York–Mollié model, MCMC.
	BibTeX: @INPROCEEDINGS{Flur:Furr:19, AUTHOR = {Roman Flury and Reinhard Furrer}, TITLE = {Multiresolution Decomposition of Areal Count Data}, BOOKTITLE = {Proceedings of the GRASPA 2019 Conference, Pescara, 15-16 July 2019}, YEAR = {2019}, EDITOR = {Michela Cameletti and Luigi Ippoliti and Alessio Pollice}, PAGES = {86--89}, DOI = {10.6092/GRASPA19_pp86-89}, KEYWORDS = {Spatial scales, Lattice data, Intrinsic GMRF, Besag--York--Molli{\'e} model, MCMC}, ADDRESS = {Bergamo}, PUBLISHER = {Universit{\`a} degli Studi di Bergamo}, ISBN = {978-88-97413-34-9}, DISPLAY = {Flury, R. and Furrer, R. (2021). Multiresolution Decomposition of Areal Count Data. In: Cameletti, M., Ippoliti, L., and Pollice, A. (eds.) Proceedings of the GRASPA 2019 Conference, Pescara, 15–16 July 2019, pp. 86–89.}, }
	Noll, S., Furrer, R., Reiser, B., and Nakas C. T. (2019). Inference in ROC surface analysis via a trinormal model-based testing approach. Stat, 8(1), e249. [Abstract] [BibTeX]
	Abstract: Receiver Operating Characteristic (ROC) analysis is the methodological framework of choice for the assessment of diagnostic markers and classification procedures in general, in both two-class and multiple-class classification problems. We focus on the three-class problem for which inference usually involves formal hypothesis testing using a proxy metric such as the Volume Under the ROC Surface (VUS). In this article we develop on an existing approach from the two-class ROC framework. We define a hypothesis testing procedure that directly compares two ROC surfaces under the assumption of the trinormal model. In the case of the assessment of a single marker the corresponding ROC surface is compared to the chance plane, i.e. to an uninformative marker. A simulation study investigating the proposed tests with existing ones based on the VUS metric follows. Finally, the proposed methodology is applied to a dataset of a panel of Pancreatic cancer diagnostic markers. The described testing procedures along with related graphical tools are supported in the corresponding R-package trinROC which we have developed for this purpose. Keywords: Delta Method; ROC Analysis; Trinormal ROC Model; Volume Under the ROC Surface (VUS); Box-Cox transformation; Pancreatic Cancer Biomarkers
	BibTeX: @ARTICLE{Noll:Furr:Reis:Naka:19, AUTHOR = {Samuel Noll and Reinhard Furrer and Benjamin Reiser and Christos T Nakas}, TITLE = {Inference in ROC surface analysis via a trinormal model-based testing approach}, JOURNAL = {Stat}, FJOURNAL = {Stat}, YEAR = {2019}, DOI = {10.1002/sta4.249}, VOLUME = {8}, NUMBER = {1}, PAGES = {e249}, FUNDING = {Israel Science Foundation, 387/15}, DISPLAY = {Noll, S., Furrer, R., Reiser, B., and Nakas C. T. (2019). Inference in ROC surface analysis via a trinormal model-based testing approach. Stat, 8(1), e249.}, }
	Gerber, F. and Furrer, R. (2019). optimParallel: An R Package Providing a Parallel Version of the L-BFGS-B Optimization Method. The R Journal, 11(1), 352–358. [Abstract] [BibTeX]
	Abstract: The R package optimParallel provides a parallel version of the L-BFGS-B optimization method of optim. The main function of the package is optimParallel(), which has the same usage and output as optim(). Using optimParallel() can significantly reduce the optimization time, especially when the evaluation time of the objective function is large and no analytical gradient is available. We introduce the R package and illustrate its implementation, which takes advantage of the lexical scoping mechanism of R.
	BibTeX: @ARTICLE{Gerb:Furr:19, AUTHOR = {Gerber, F., and Furrer, R.}, TITLE = {optimParallel: An R Package Providing a Parallel Version of the L-BFGS-B Optimization Method}, JOURNAL = {R Journal}, FJOURNAL = {The R Journal}, YEAR = {2019}, DOI = {10.32614/RJ-2019-030}, VOLUME = {11}, NUMBER = {1}, PAGES = {352--358}, FUNDING = {}, DISPLAY = {Gerber, F. and Furrer, R. (2019). optimParallel: An R Package Providing a Parallel Version of the L-BFGS-B Optimization Method. The R Journal, 11(1), 352–358.}, }
	Kratzer, G., Furrer, R. and Pittavino, M. (2019). Comparison Between Suitable Priors for Additive Bayesian Networks. In: Argiento R., Durante D., Wade S. (eds.) Bayesian Statistics and New Generations. BAYSM 2018. Springer Proceedings in Mathematics & Statistics, vol 296. Springer-Verlag, pp. 95–104. [Abstract] [BibTeX]
	Abstract: Additive Bayesian networks (ABN) are types of graphical models that extend the usual Bayesian-generalised linear model to multiple dependent variables through the factorisation of the joint probability distribution of the underlying variables. When fitting an ABN model, the choice of the prior for the parameters is of crucial importance. If an inadequate prior—like a not sufficiently informative one—is used, data separation and data sparsity may lead to issues in the model selection process. In this work we present a simulation study to compare two weakly informative priors with a strongly informative one. For the weakly informative prior, we use a zero mean Gaussian prior with a large variance, currently implemented in the R package abn. The candidate prior belongs to the Student’s t-distribution. It is specifically designed for logistic regressions. Finally, the strongly informative prior is Gaussian with a mean equal to the true parameter value and a small variance. We compare the impact of these priors on the accuracy of the learned additive Bayesian network as function of different parameters. We create a simulation study to illustrate Lindley’s paradox based on the prior choice. We then conclude by highlighting the good performance of the informative Student’s t-prior and the limited impact of Lindley’s paradox. Finally, suggestions for further developments are provided. Keywords: Graph theory, Structural search, Binomial regression
	BibTeX: @Proceedings{Krat:Furr:Pitt:19, TITLE = {Comparison Between Suitable Priors for Additive Bayesian Networks}, YEAR = {2019}, AUTHOR = {Kratzer, G. and Furrer, R. and Pittavino, M.}, BOOKTITLE = {Bayesian Statistics and New Generations. BAYSM 2018}, EDITOR = {Argiento R. and Durante D. and Wade, S.}, VOLUME = {296}, PAGES = {95-104}, DOI = {10.1007/978-3-030-30611-3_10}, SERIES = {Springer Proceedings in Mathematics & Statistics}, PUBLISHER = {Springer-Verlag, Cham}, DISPLAY = {Kratzer, G., Furrer, R. and Pittavino, M. (2019). Comparison Between Suitable Priors for Additive Bayesian Networks. In: Argiento R., Durante D., Wade S. (eds.) Bayesian Statistics and New Generations. BAYSM 2018. Springer Proceedings in Mathematics & Statistics, vol 296. Springer-Verlag, pp. 95–104.}, }
	Alegría, A., Porcu, E., Furrer, R. and Mateu, J. (2019). Covariance functions for multivariate Gaussian fields evolving temporally over planet earth. Stochastic Environmental Research and Risk Assessment, 33(8–9), 1593–1608. [Abstract] [BibTeX]
	Abstract: The construction of valid and flexible cross-covariance functions is a fundamental task for modeling multivariate space–time data arising from, e.g., climatological and oceanographical phenomena. Indeed, a suitable specification of the covariance structure allows to capture both the space–time dependencies between the observations and the development of accurate predictions. For data observed over large portions of planet earth it is necessary to take into account the curvature of the planet. Hence the need for random field models defined over spheres across time. In particular, the associated covariance function should depend on the geodesic distance, which is the most natural metric over the spherical surface. In this work, we propose a flexible parametric family of matrix-valued covariance functions, with both marginal and cross structure being of the Gneiting type. We also introduce a different multivariate Gneiting model based on the adaptation of the latent dimension approach to the spherical context. Finally, we assess the performance of our models through the study of a bivariate space–time data set of surface air temperatures and precipitable water content. Keywords: Geodesic, Gneiting classes, Latent dimensions, Precipitable water content, Space–time, Sphere, Temperature.
	BibTeX: @ARTICLE{Aleg:Porc:Furr:Mate:19, AUTHOR = {Alfredo Alegría and Emilio Porcu and Reinhard Furrer and Jorge Mateu}, TITLE = {Covariance functions for multivariate Gaussian fields evolving temporally over planet earth}, JOURNAL = {Stoch. Environ. Res. Risk Assess.}, FJOURNAL = {Stochastic Environmental Research and Risk Assessment}, YEAR = {2019}, DOI = {10.1007/s00477-019-01707-w}, VOLUME = {33}, NUMBER = {8--9}, PAGES = {1593--1608}, FUNDING = {SNSF-144973 and SNSF-175529 and more}, DISPLAY = {Alegría, A., Porcu, E., Furrer, R. and Mateu, J. (2019). Covariance functions for multivariate Gaussian fields evolving temporally over planet earth. Journal, 33(8–9), 1593–1608.}, }
	Brunner, M. I., Bárdossy, A., and Furrer, R. (2019). Technical note: Stochastic simulation of streamflow time series using phase randomization. Hydrology and Earth Systems Science, 23, 3175–3187. [Abstract] [BibTeX] [R-Package]
	Abstract: Stochastically generated streamflow time series are widely used in water resource planning and management. Such series represent sets of plausible yet unobserved streamflow realizations which should reproduce the main characteristics of observed data. These characteristics include the distribution of daily streamflow values and their temporal correlation as expressed by short- and long-range dependence. Existing streamflow generation approaches have mainly focused on the time domain, even though simulation in the frequency domain provides good properties. These properties comprise the simulation of both short- and long-range dependence as well as extension to multiple sites. Simulation in the frequency domain is based on the randomization of the phases of the Fourier transformation. We here combine phase randomization simulation with a flexible, four-parameter kappa distribution, which allows for the extrapolation to as yet unobserved low and high flows. The simulation approach consists of seven steps: (1) fitting the theoretical kappa distribution, (2) normalization and deseasonalization of the marginal distribution, (3) Fourier transformation, (4) random phase generation, (5) inverse Fourier transformation, (6) back transformation, and (7) simulation. The simulation approach is applicable to both individual and multiple sites. It was applied to and validated on a set of four catchments in Switzerland. Our results show that the stochastic streamflow generator based on phase randomization produces realistic streamflow time series with respect to distributional properties and temporal correlation. However, cross-correlation among sites was in some cases found to be underestimated. The approach can be recommended as a flexible tool for various applications such as the dimensioning of reservoirs or the assessment of drought persistence.
	BibTeX: @ARTICLE{Brun:Bard:Furr:19, AUTHOR = {Brunner, M. I. and Bárdossy, A. and Furrer, R.}, TITLE = {Technical note: Stochastic simulation of streamflow time series using phase randomization}, JOURNAL = {Hydrol. Earth Syst. Sci.}, FJOURNAL = {Hydrology and Earth Systems Science}, YEAR = {2019}, DOI = {10.5194/hess-23-3175-2019}, VOLUME = {23}, PAGES = {3175--3187}, FUNDING = {Swiss Federal Office for the Environment (FOEN) (grant no. 15.0003.PJ/Q292-5096), the Deutsche Forschungsgemeinschaft (DFG) (grant no. Ba-1150/13-1), and the Swiss National Science Foundation (SNF) (grant no. 175529).}, DISPLAY = {Brunner, M. I., Bárdossy, A., and Furrer, R. (2019). Technical note: Stochastic simulation of streamflow time series using phase randomization. Hydrology and Earth Systems Science, 23, 3175–3187.}, }
	Hartnack, S., Odoch, T., Kratzer, G., Furrer, R., Wasteson, Y., L'Abée-Lund, T. M., and Skjerve, E. (2019). Additive Bayesian networks for antimicrobial resistance and potential risk factors in non-typhoidal Salmonella isolates from layer hens in Uganda. BMC Veterinary Research, 15:212, 1–9. [Abstract] [BibTeX]
	Abstract: Background: Multi-drug resistant bacteria are seen increasingly and there are gaps in our understanding of the complexity of antimicrobial resistance, partially due to a lack of appropriate statistical tools. This hampers efficient treatment, precludes determining appropriate intervention points and renders prevention very difficult. Methods: We re-analysed data from a previous study using additive Bayesian networks. The data contained information on resistances against seven antimicrobials and seven potential risk factors from 86 non-typhoidal Salmonella isolates from laying hens in 46 farms in Uganda. Results: The final graph contained 22 links between risk factors and antimicrobial resistances. Solely ampicillin resistance was linked to the vaccinating person and disposal of dead birds. Systematic associations between ampicillin and sulfamethoxazole/trimethoprim and chloramphenicol, which was also linked to sulfamethoxazole/trimethoprim were detected. Sulfamethoxazole/trimethoprim was also directly linked to ciprofloxacin and trimethoprim. Trimethoprim was linked to sulfonamide and ciprofloxacin, which was also linked to sulfonamide. Tetracycline was solely linked to ciprofloxacin. Conclusions: Although the results needs to be interpreted with caution due to a small data set, additive Bayesian network analysis allowed a description of a number of associations between the risk factors and antimicrobial resistances investigated. Keywords: Keywords: Salmonella, Antimicrobial resistance, Multi-drug resistance, Patterns of antimicrobial resistance
	BibTeX: @ARTICLE{Hart:etal:19, AUTHOR = {Sonja Hartnack and Terence Odoch and Gilles Kratzer and Reinhard Furrer and Yngvild Wasteson and Trine M. L'Abée-Lund and Eystein Skjerve}, TITLE = {Additive Bayesian networks for antimicrobial resistance and potential risk factors in non-typhoidal \emph{Salmonella} isolates from layer hens in Uganda}, JOURNAL = {BMC Vet. Res.}, FJOURNAL = {BMC Veterinary Research}, YEAR = {2019}, DOI = {10.1186/s12917-019-1965-y}, VOLUME = {15:212}, NUMBER = {}, PAGES = {1--9}, FUNDING = {Div}, DISPLAY = {Hartnack, S., Odoch, T., Kratzer, G., Furrer, R., Wasteson, Y., L'Abée-Lund, T. M., and Skjerve, E. (2019). Additive Bayesian networks for antimicrobial resistance and potential risk factors in non-typhoidal Salmonella isolates from layer hens in Uganda. BMC Veterinary Research, 15:212, 1–9.}, }
	Braun, D., de Jong, R., Schaepman, M. E., Furrer, R., Hein, L., Kienast, F., and Damm, A. (2019). Ecosystem service change caused by climatological and non-climatological drivers: A Swiss case study. Ecological Applications, 29(4), e01901. [Abstract] [BibTeX]
	Abstract: Understanding the drivers of ecosystem change and their effects on ecosystem services are essential for management decisions and verification of progress towards national and international sustainability policies (e.g. Aichi Biodiversity Targets, Sustainable Development Goals). We aim to disentangle spatially the effect of climatological and non-climatological drivers on ecosystem service supply and trends. Therefore, we explored time series of three ecosystem services in Switzerland between 2004 and 2014: carbon dioxide regulation, soil erosion prevention, and air quality regulation. We applied additive models to describe the spatial variation attributed to climatological (i.e. temperature, precipitation and relative sunshine duration) and non-climatological drivers (i.e. random effects representing other spatially structured processes) that may affect ecosystem service change. Obtained results indicated strong influences of climatological drivers on ecosystem service trends in Switzerland. We identified equal contributions of all three climatological drivers on trends of carbon dioxide regulation and soil erosion prevention, while air quality regulation was more strongly influenced by temperature. Additionally, our results showed that climatological and non-climatological drivers affected ecosystem services both negatively and positively, depending on the regions (in particular lower and higher altitudinal areas), drivers, and services assessed. Our findings highlight stronger effects of climatological compared to non-climatological drivers on ecosystem service change in Switzerland. Furthermore, drivers of ecosystem change display a spatial heterogeneity in their influence on ecosystem service trends. We propose an approach building on an additive model to disentangle the effect of climatological and non-climatological drivers on ecosystem service trends. Such analyses should be extended in the future to ecosystem service flow and demand to complete ecosystem service assessments and to demonstrate and communicate more clearly the benefits of ecosystem services for human well-being. Keywords: Regulating services, remote sensing, time series, trends, climate change, land use change.
	BibTeX: @ARTICLE{Brau:etal:19, AUTHOR = {Braun, Daniela and de Jong, Rogier and Schaepman, Michael and Furrer, Reinhard and Hein, Lars and Kienast, Felix and Damm, Alexander}, TITLE = {Ecosystem service change caused by climatological and non-climatological drivers: A Swiss case study}, JOURNAL = {Ecol. Appl.}, FJOURNAL = {Ecological Applications}, YEAR = {2019}, DOI = {10.1002/eap.1901}, VOLUME = {29}, NUMBER = {4}, PAGES = {e01901}, FUNDING = {URPP-GCB, more}, DISPLAY = {Braun, D., de Jong, R., Schaepman, M. E., Furrer, R., Hein, L., Kienast, F., and Damm, A. (2019). Ecosystem service change caused by climatological and non-climatological drivers: A Swiss case study. Ecological Applications, 29(4), e01901.}, }
	Ruchti, S., Kratzer, G., Furrer, R., Hartnack, S., Würbel, H. and Gebhardt–Henrich, S. G. (2019). Progression and risk factors of pododermatitis in part-time group housed rabbit does in Switzerland. Preventive Veterinary Medicine, 166, 56–64. [Abstract] [BibTeX]
	Abstract: In rabbits (Oryctolagus cuniculus L.), pododermatitis is a chronic multifactorial skin disease that appears mainly on the plantar surface of the hind legs. This presumably progressive disease can cause pain leading to poor welfare, yet the progression of this disease has not been thoroughly assessed on the level of individual animals. The aim of this longitudinal study thus was to investigate the possible risk factors and the progression of pododermatitis in group housed breeding does in Switzerland on litter and plastic slats. Three commercial rabbit farms with part-time group housing on litter and plastic slats were visited every four weeks throughout one year. During every visit, the same 201 adult female breeding rabbits (67 does per farm) were evaluated for the presence and severity of pododermatitis. Additionally, the does? age, parity, body weight, reproductive state, hybrid, claw length, cleanliness and moisture of the paws and the temperature and humidity inside the barns were recorded as potential risk factors. The risk factors were analysed through general linear models and additive Bayesian network (ABN) modelling using a directed acyclic graph (DAG) for visualising associations between potential risk factors. The progression of pododermatitis was analysed with a transition matrix. Relative humidity inside the barns, body weight, number of kindlings, age, and claw length were the most important risk factors, all being positively associated with pododermatitis. In contrast to expectations, the cleanliness of the left hind paw was negatively associated with the occurrence of pododermatitis, but the effect was small. In young does, the severity of pododermatitis quickly increased and in some rabbits proceeded to ulcerated spots. It was shown that 60.00%, 14.17% and 3.33% of ulcerated lesions recovered to a state without ulceration within 4, 8 or >12 weeks, respectively. Keywords: Rabbit, group housing, pododermatitis, risk factors, progression, additive Bayesian network modelling
	BibTeX: @ARTICLE{Ruch:etal:19, AUTHOR = {Sabrina Ruchti and Gilles Kratzer and Reinhard Furrer and Sonja Hartnack and Hanno Würbel and Sabine G. Gebhardt--Henrich}, TITLE = {Progression and risk factors of pododermatitis in part-time group housed rabbit does in Switzerland}, JOURNAL = {Prev. Vet. Med.}, FJOURNAL = {Preventive Veterinary Medicine}, YEAR = {2019}, DOI = {10.1016/j.prevetmed.2019.01.013}, VOLUME = {166}, NUMBER = {May}, PAGES = {56--64}, FUNDING = {Diverse}, DISPLAY = {Ruchti, S., Kratzer, G., Furrer, R., Hartnack, S., Würbel, H. and Gebhardt-Henrich, S. G. (2019). Progression and risk factors of pododermatitis in part-time group housed rabbit does in Switzerland. Preventive Veterinary Medicine, 166, 56–64.}, }
	Wang, C. and Furrer, R. (2019). Efficient inference of generalized spatial fusion models with flexible specification. Stat, 8(1), e216. [Abstract] [BibTeX] [Code 1, Code 2]
	Abstract: In spatial statistics, data are often collected at different spatial resolutions. Often, it is of interest to (a) carry out multivariate analysis when variables are sampled at different locations, (b) model data collected at misaligned areas, or (c) unravel common latent factors by jointly modelling point and areal data. In this paper, we establish a linkage between the generalized spatial fusion model framework and the various change-of-support problems, and we outline how the framework can be adapted in these situations. Moreover, we propose an efficient fusion model implementation by exploiting advantages of nearest neighbour Gaussian process and the Stan modelling language. Our simulation shows that the computational efficiency is several times higher in the new implementation compared with the original implementation. We illustrate the performance gain in practice using a case study, which models daily precipitation in Switzerland based on rain gauge and radar data. Keywords: change-of-support problem; data fusion; ecological bias; latent spatial process; non-centered parameterization
	BibTeX: @ARTICLE{Wang:Furr:19, AUTHOR = {Craig Wang and Reinhard Furrer}, TITLE = {Efficient inference of generalized spatial fusion models with flexible specification}, JOURNAL = {Stat}, FJOURNAL = {Stat}, YEAR = {2019}, DOI = {10.1002/sta4.216}, VOLUME = {8}, NUMBER = {1}, PAGES = {e216}, FUNDING = {SNSF-175529}, DISPLAY = {Wang, C. and Furrer, R. (2019). Efficient inference of generalized spatial fusion models with flexible specification. Stat, 8(1), e216.}, }
	Bevilacqua, M., Faouzi, T., Furrer, R. and Porcu, E. (2019). Estimation and prediction using generalized Wendland covariance functions under fixed domain asymptotics. The Annals of Statistics, 47(2), 828–856. [PDF] [Abstract] [BibTeX]
	Abstract: We study estimation and prediction of Gaussian random fields with covariance models belonging to the generalized Wendland (GW) class, under fixed domain asymptotics. As for the Matérn case, this class allows for a continuous parameterization of smoothness of the underlying Gaussian random field, being additionally compactly supported. The paper is divided into three parts: first, we characterize the equivalence of two Gaussian measures with GW covariance function, and we provide sufficient conditions for the equivalence of two Gaussian measures with Matérn and GW covariance functions. In the second part, we establish strong consistency and asymptotic distribution of the maximum likelihood estimator of the microergodic parameter associated to GW covariance model, under fixed domain asymptotics. The third part elucidates the consequences of our results in terms of (misspecified) best linear unbiased predictor, under fixed domain asymptotics. Our findings are illustrated through a simulation study: the former compares the finite sample behavior of the maximum likelihood estimation of the microergodic parameter with the given asymptotic distribution. The latter compares the finite-sample behavior of the prediction and its associated mean square error when using two equivalent Gaussian measures with Matérn and GW covariance models, using covariance tapering as benchmark. Keywords: Compactly supported covariance, spectral density, large dataset, microergodic parameter.
	BibTeX: @ARTICLE{Bevi:Faou:Furr:Porc:19, AUTHOR = {Moreno Bevilacqua and Tarik Faouzi and Reinhard Furrer and Emilio Porcu}, TITLE = {Estimation and prediction using generalized Wendland covariance functions under fixed domain asymptotics}, JOURNAL = {Ann. Statist.}, FJOURNAL = {The Annals of Statistics}, YEAR = {2019}, DOI = {10.1214/17-AOS1652}, VOLUME = {47}, NUMBER = {2}, PAGES = {828--856}, FUNDING = {URPP-GCB and SNSF-175529}, DISPLAY = {Bevilacqua, M., Faouzi, T., Furrer, R. and Porcu, E. (2019). Estimation and prediction using generalized Wendland covariance functions under fixed domain asymptotics. The Annals of Statistics, 47(2), 828–856.}, }
	Heaton, M. J., Datta, A., Finley, A. O., Furrer, R., Guiness, J., Guhaniyogi, R., Gerber, F., Gramacy, R. B., Hammerling, D., Katzfuss, M., Lindgren, F., Nychka, D. W., Sun, F., and Zammit-Mangion A. (2019). A Case Study Competition Among Methods for Analyzing Large Spatial Data, Journal of Agricultural, Biological, and Environmental Statistics, 24(3), 398–425. Software available via: github.com/finnlindgren/heatoncomparison. [Abstract] [BibTeX]
	Abstract: The Gaussian process is an indispensable tool for spatial data analysts. The onset of the ``big data'' era, however, has lead to the traditional Gaussian process being computationally infeasible for modern spatial data. As such, various alternatives to the full Gaussian process that are more amenable to handling big spatial data have been proposed. These modern methods often exploit low-rank structures and/or multi-core and multi-threaded computing environments to facilitate computation. This study provides, first, an introductory overview of several methods for analyzing large spatial data. Second, this study describes the results of a predictive competition among the described methods as implemented by different groups with strong expertise in the methodology. Specifically, each research group was provided with two training datasets (one simulated and one observed) along with a set of prediction locations. Each group then wrote their own implementation of their method to produce predictions at the given location and each was subsequently run on a common computing environment. The methods were then compared in terms of various predictive diagnostics. Supplementary materials regarding implementation details of the methods and code are available for this article online. Keywords: Big data, Gaussian process, Parallel computing, Low-rank approximation.
	BibTeX: @ARTICLE{Heat::Furr::19, AUTHOR = {Heaton, Matthew J. and Datta, Abhirup and Finley, Andrew O. and Furrer, Reinhard and Guinness, Joseph and Guhaniyogi, Rajarshi and Gerber, Florian and Gramacy, Robert B. and Hammerling, Dorit and Katzfuss, Matthias and Lindgren, Finn and Nychka, Douglas W. and Sun, Furong and Zammit-Mangion, Andrew}, TITLE = {A Case Study Competition Among Methods for Analyzing Large Spatial Data}, JOURNAL = {J. Agric. Biol. Environ. Stat.}, FJOURNAL = {Journal of Agricultural, Biological and Environmental Statistics}, YEAR = {2019}, DOI = {10.1007/s13253-018-00348-w}, VOLUME = {24}, NUMBER = {3}, PAGES = {398–425}, FUNDING = {SNSF Grant 175529, URPP and from others}, DISPLAY = {Heaton, M. J., Datta, A., Finley, A. O., Furrer, R., Guiness, J., Guhaniyogi, R., Gerber, F., Gramacy, R. B., Hammerling, D., Katzfuss, M., Lindgren, F., Nychka, D. W., Sun, F., and Zammit-Mangion A. (2019). A Case Study Competition Among Methods for Analyzing Large Spatial Data, Journal of Agricultural, Biological, and Environmental Statistics, 24(3), 398–425.}, }
	Brunner, M. I., Furrer, R., and Favre, A.-C. (2019). Modeling the spatial dependence of floods using the Fisher copula. Hydrology and Earth System Sciences, 23(1), 107–124. [Abstract] [BibTeX]
	Abstract: Floods often affect not only a single location, but also a whole region. Flood frequency analysis should therefore be undertaken at a regional scale which requires the considerations of the dependence of events at different locations. This dependence is often neglected even though its consideration is essential to derive reliable flood estimates. A model used in regional multivariate frequency analysis should ideally consider the dependence of events at multiple sites which might show dependence in the lower and/or upper tail of the distribution. We here seek to propose a simple model that on the one hand considers this dependence with respect to the network structure of the region and on the other hand allows for the simulation of stochastic event sets at both gauged and ungauged locations. The new Fisher copula model is used for representing the spatial dependence of flood events in the nested Thur catchment in Switzerland. Flood event samples generated for the gauged stations using the Fisher copula are compared to samples generated by other dependence models allowing for modeling of multivariate data including elliptical copulas, R-vine copulas, and max-stable models. The comparison of the dependence structures of the generated samples shows that the Fisher copula is a suitable model for capturing the spatial dependence in the data. We therefore use the copula in a way such that it can be used in an interpolation context to simulate event sets comprising gauged and ungauged locations. The spatial event sets generated using the Fisher copula well capture the general dependence structure in the data and the upper tail dependence, which is of particular interest when looking at extreme flood events and when extrapolating to higher return periods. The Fisher copula was for a medium-sized catchment found to be a suitable model for the stochastic simulation of flood event sets at multiple gauged and ungauged locations.
	BibTeX: @ARTICLE{Brun:Furr:Favr:19, AUTHOR = {Brunner, M. I. and Furrer, R. and Favre, A.-C.}, TITLE = {Modeling the spatial dependence of floods using the Fisher copula}, JOURNAL = {Hydrol. Earth Syst. Sci.}, FJOURNAL = {Hydrology and Earth System Sciences}, YEAR = {2019}, DOI = {10.5194/hess-23-107-2019}, VOLUME = {23}, NUMBER = {1}, PAGES = {107--124}, FUNDING = {FOEN: contract 13.0028.KP/M285-0623}, DISPLAY = {Brunner, M. I., Furrer, R., and Favre, A.-C. (2019). Modeling the spatial dependence of floods using the Fisher copula. Hydrology and Earth System Sciences, 23(1), 107–124.}, }
	Emery, X., Furrer, R. and Porcu, E. (2019). A Turning Bands Method for Simulating Isotropic Gaussian Random Fields on the Sphere. Statistics and Probability Letters, 144, 9–15. [Abstract] [BibTeX]
	Abstract: We introduce a novel approach to simulate Gaussian random fields defined over spheres of \R^3. Through continuation we embed the process on the sphere in a nonstationary random field of \R^3 to use a turning bands method. We also discuss the approximation accuracy. Keywords: Covariance functions, Great circle, Spheres, Turning bands.
	BibTeX: @ARTICLE{Emer:Furr:Porc:19, AUTHOR = {Emery, X. and Furrer, R. and Porcu, E.}, TITLE = {A Turning Bands Method for Simulating Isotropic Gaussian Random Fields on the Sphere}, JOURNAL = {Statist. Probab. Lett.}, FJOURNAL = {Statistics and Probability Letters}, YEAR = {2019}, DOI = {10.1016/j.spl.2018.07.017}, VOLUME = {144}, PAGES = {9--15}, FUNDING = {SNSF-175529, CONICYT/FONDECYT 1170290.}, DISPLAY = {Emery, X., Furrer, R. and Porcu, E. (2019). A Turning Bands Method for Simulating Isotropic Gaussian Random Fields on the Sphere. Statistics and Probability Letters, 144, 9–15.}, }

2018

	Sain, S. R. and Furrer, R. (2018). Comments on: Some recent work on multivariate Gaussian Markov random fields. TEST, 27(3), 545–548. [Abstract] [BibTeX]
	In Some recent work on multivariate Gaussian Markov random fields, author Ying C. MacNab unifies several lines of research focused on multivariate formulations of Gaussian Markov random field (MRF) models through a coregionalization framework. MRFs are natural models for data on regular or irregular lattices, and, as the author has noted, they have found application in a wide range of scientific areas. There are significant computational advantages to MRFs that allow consideration of much larger datasets, but there are also a number of other challenges that arise with such models. The author specifically addresses two of these, namely the entanglement of spatial and non-spatial components and the enforcement for positivity condition. Multivariate Gaussian MRFs involve the specification of a precision matrix that encompasses both the dependence between variables and the spatial dependence across location. This precision matrix is often sparse, which enables the use of sparse matrix methods to improve computational performance. However, these precision matrices have very complex structure and parameterizations, which leads to the noted issues with entanglement of the spatial and non-spatial components and difficulty with ensuring these matrices are positive definite. While the paper yields a great deal of information about these issues, there are some practical concerns for those interested in using such models that are also important. We comment on those in the following section. Next, against a statement made in the paper, the model of Sain et al. (2011) does allow a separable structure as we show. ...
	BibTeX: @ARTICLE{Sain:Furr:18, AUTHOR = {Sain, S. R. and Furrer, R.}, TITLE = {Comments on: Some recent work on multivariate {Gaussian} {Markov} random fields}, JOURNAL = {Test}, FJOURNAL = {Test}, YEAR = {2018}, DOI = {10.1007/s11749-018-0605-3}, VOLUME = {27}, NUMBER = {3}, PAGES = {545--548}, FUNDING = {}, DISPLAY = {Sain, S. R. and Furrer, R. (2018). Comments on: Some recent work on multivariate Gaussian Markov random fields. TEST, 27(3), 545–548}, }
	Brunner, M., Sikorska, A. E., Furrer, R. and Favre, A.-C. (2018). Uncertainty assessment of synthetic design hydrographs for gauged and ungauged catchments. Water Resources Research, 54(3), 1493–1512. [Abstract] [BibTeX]
	Abstract: Design hydrographs described by peak discharge, hydrograph volume, and hydrograph shape are essential for engineering tasks involving storage. Such design hydrographs are inherently uncertain as are classical flood estimates focusing on peak discharge only. Various sources of uncertainty contribute to the total uncertainty of synthetic design hydrographs for gauged and ungauged catchments. These comprise model uncertainties, sampling uncertainty, and uncertainty due to the choice of a regionalization method. A quantification of the uncertainties associated with flood estimates is essential for reliable decision making and allows for the identification of important uncertainty sources. We therefore propose an uncertainty assessment framework for the quantification of the uncertainty associated with synthetic design hydrographs. The framework is based on bootstrap simulations and consists of three levels of complexity. On the first level, we assess the uncertainty due to individual uncertainty sources. On the second level, we quantify the total uncertainty of design hydrographs for gauged catchments and the total uncertainty of regionalizing them to ungauged catchments but independently from the construction uncertainty. On the third level, we assess the coupled uncertainty of synthetic design hydrographs in ungauged catchments, jointly considering construction and regionalization uncertainty. We find that the most important sources of uncertainty in design hydrograph construction are the record length and the choice of the flood sampling strategy. The total uncertainty of design hydrographs in ungauged catchments depends on the catchment properties and is not negligible in our case.
	BibTeX: @ARTICLE{Brun:Siko:Furr:Favr:18, AUTHOR = {Brunner, M. and Sikorska, A. E. and Furrer, R. and Favre, A.-C.}, TITLE = {Uncertainty assessment of synthetic design hydrographs for gauged and ungauged catchments}, JOURNAL = {Water Resour. Res.}, FJOURNAL = {Water Resources Research}, YEAR = {2018}, DOI = {10.1002/2017WR021129}, VOLUME = {54}, NUMBER = {3}, PAGES = {1493-1512}, FUNDING = {FOEN, BAFU, MeteoSwiss, ...}, DISPLAY = {Brunner, M., Sikorska, A. E., Furrer, R. and Favre, A.-C. (2018). Uncertainty assessment of synthetic design hydrographs for gauged and ungauged catchments. Water Resources Research, 54(3), 1493–1512.}, }
	Wang, C., Torgerson, P. R., Kaplan, R. M., George, M. M. and Furrer, R. (2018). Modelling anthelmintic resistance by extending eggCounts package to allow individual efficacy. International Journal for Parasitology: Drugs and Drug Resistance, 8(3), 386–393. [Abstract] [BibTeX]
	Abstract: The same anthelmintic treatment can have variable efficacy on individual animals even if the parasite population is homogenously susceptible. An extension of the R package eggCounts is proposed to take individual efficacy into account using a Bayesian hierarchical model. A simulation study is conducted to compare the performance of five different methods on estimating faecal egg count reduction and its uncertainty interval. Simulation results showed the individual efficacy model offered robust inference to two different data simulation procedures with low root mean squared error on the reduction estimate and appropriate uncertainty estimates. Different methods were used to evaluate the anthelmintic resistance in a dataset from USA with sheep and cattle faecal egg counts, where a strong anthelmintic resistance was detected. Open-source statistical tools were updated to include the proposed model. Keywords: Bayesian hierarchical model; statistical analysis; faecal egg count reduction test; anthelmintic resistance; simulation study.
	BibTeX: @ARTICLE{Wang:etal:Furr:18, AUTHOR = {Craig Wang and Paul R. Torgerson and Ray M. Kaplan and Melissa M. George and Reinhard Furrer}, TITLE = {Modelling anthelmintic resistance by extending eggCounts package to allow individual efficacy}, JOURNAL = {Int. J. Parasitol. Drug.}, FJOURNAL = {International Journal for Parasitology: Drugs and Drug Resistance}, YEAR = {2018}, DOI = {10.1016/j.ijpddr.2018.07.003 }, VOLUME = {8}, NUMBER = {3}, PAGES = {386-393}, PMID = {30103206}, PMCID = {PMC 6091319}, FUNDING = {SNSF-175529}, DISPLAY = {Wang, C., Torgerson, P. R., Kaplan, R. M., George, M. M. and Furrer, R. (2018). Modelling anthelmintic resistance by extending eggCounts package to allow individual efficacy. International Journal for Parasitology: Drugs and Drug Resistance, 8(3), 386–393.}, }
	Porcu, E., Alegria, A. and Furrer, R. (2018). Modeling Temporally Evolving and Spatially Globally Dependent Data. International Statistical Review, 86, 344–377. [Abstract] [BibTeX]
	Abstract: The last decades have seen an unprecedented increase in the availability of data sets that are inherently global and temporally evolving, from remotely sensed networks to climate model ensembles. This paper provides an overview of statistical modeling techniques for space–time processes, where space is the sphere representing our planet. In particular, we make a distintion between (a) second order‐based approaches and (b) practical approaches to modeling temporally evolving global processes. The former approaches are based on the specification of a class of space–time covariance functions, with space being the two‐dimensional sphere. The latter are based on explicit description of the dynamics of the space–time process, that is, by specifying its evolution as a function of its past history with added spatially dependent noise. We focus primarily on approach (a), for which the literature has been sparse. We provide new models of space–time covariance functions for random fields defined on spheres cross time. Practical approaches (b) are also discussed, with special emphasis on models built directly on the sphere, without projecting spherical coordinates onto the plane. We present a case study focused on the analysis of air pollution from the 2015 wildfires in Equatorial Asia, an event that was classified as the year's worst environmental disaster. The paper finishes with a list of the main theoretical and applied research problems in the area, where we expect the statistical community to engage over the next decade.
	BibTeX: @ARTICLE{Porc:Aleg:Furr:18, AUTHOR = {Porcu, Emilio and Alegria, Alfredo and Furrer, Reinhard}, TITLE = {Modeling Temporally Evolving and Spatially Globally Dependent Data}, JOURNAL = {Int. Stat. Rev.}, FJOURNAL = {International Statistical Review}, YEAR = {2018}, DOI = {10.1111/insr.12266}, VOLUME = {86}, PAGES = {344-377}, FUNDING = {Fondecyt Regular 1170290, SNSF-175529}, DISPLAY = {Porcu, E., Alegria, A., and Furrer, R. (2018). Modeling Temporally Evolving and Spatially Globally Dependent Data. International Statistical Review, 86: 344–377.}, }
	Gerber, F., Mösinger, K., and Furrer, R. (2018). dotCall64: An R package providing an efficient interface to compiled C, C++, and Fortran code supporting long vectors. SoftwareX, 7, 217–221. [Abstract] [BibTeX]
	Abstract: The R package dotCall64 provides an enhanced version of the foreign function interface (FFI) to call compiled C, C++, and Fortran code from the software environment R. It allows users to integrate compiled code without using complex application programming interfaces (APIs), such as the C API of R. Moreover, dotCall64 supports long vectors having more than 2^{31}-1 elements and implements a mechanism to avoid unnecessary copies of R objects. Therefore, dotCall64 facilitates making existing C, C++, and Fortran libraries accessible for R and is particularly useful for applications involving long vectors. Keywords: Foreign function interface; 64-bit; Large datasets.
	BibTeX: @ARTICLE{Gerb:Moes:Furr:18, AUTHOR = {Florian Gerber and Kaspar M\"osinger and Reinhard Furrer}, TITLE = {dotCall64: An R package providing an efficient interface to compiled C, C++, and Fortran code supporting long vectors}, JOURNAL = {SoftwareX}, FJOURNAL = {SoftwareX}, YEAR = {2018}, DOI = {10.1016/j.softx.2018.06.002}, VOLUME = {7}, PAGES = {217-221}, FUNDING = {URPP GCB}, DISPLAY = {Gerber, F., Mösinger, K., and Furrer, R. (2018). dotCall64: An R package providing an efficient interface to compiled C, C++, and Fortran code supporting long vectors. SoftwareX, 7, 217–221.}, }
	Brunner, M., Furrer, R., Sikorska, A. E., Viviroli, D., Seibert, J. and Favre Pugin, A.-C. (2018). Synthetic design hydrographs for ungauged catchments. A comparison of regionalization methods. Stochastic Environmental Research and Risk Assessment, 32(7), 1993–2023. [Abstract] [BibTeX]
	Abstract: Design flood estimates for a given return period are required in both gauged and ungauged catchments for hydraulic design and risk assessments. Contrary to classical design estimates, synthetic design hydrographs provide not only information on the peak magnitude of events but also on the corresponding hydrograph volumes together with the hydrograph shapes. In this study, we tested different regionalization approaches to transfer parameters of synthetic design hydrographs from gauged to ungauged catchments. These approaches include classical regionalization methods such as linear regression techniques, spatial methods, and methods based on the formation of homogeneous regions. In addition to these classical approaches, we tested nonlinear regression models not commonly used in hydrological regionalization studies, such as random forest, bagging, and boosting. We found that parameters related to the magnitude of the design event can be regionalized well using both linear and nonlinear regression techniques using catchment area, length of the main channel, maximum precipitation intensity, and relief energy as explanatory variables. The hydrograph shape, however, was found to be more difficult to regionalize due to its high variability within a catchment. Such variability might be better represented by looking at flood-type specific synthetic design hydrographs. Keywords: Regionalization; Ungauged catchments; Design hydrographs; Flood estimation; Regression trees.
	BibTeX: @ARTICLE{Brun:Furr:etal:18, AUTHOR = {Manuela Brunner and Reinhard Furrer and Anna E. Sikorska and Daniel Viviroli and Jan Seibert and Anne-Catherine Favre Pugin}, TITLE = {Synthetic design hydrographs for ungauged catchments. A comparison of regionalization methods}, JOURNAL = {Stoch. Environ. Res. Risk Assess.}, FJOURNAL = {Stochastic Environmental Research and Risk Assessment}, YEAR = {2018}, DOI = {10.1007/s00477-018-1523-3}, VOLUME = {32}, NUMBER = {7}, PAGES = {1993-2023}, FUNDING = {FOEN and div}, DISPLAY = {Brunner, M., Furrer, R., Sikorska, A. E., Viviroli, D., Seibert, J. and Favre Pugin, A.-C. (2018). Synthetic design hydrographs for ungauged catchments. A comparison of regionalization methods. Stochastic Environmental Research and Risk Assessment, 32(7), 1993-2023.}, }
	Güsewell, S., Pietragalla, B., Gehrig, R., and Furrer, R. (2018). Representativeness of stations and reliability of data in the Swiss Phenology Network. Technical Report MeteoSwiss, 267, 100 pp. [Abstract] [BibTeX]
	Abstract: Phenological observation networks have been implemented in many countries to monitor how the timing of plant seasonal life cycles varies in space and time. Data are used to model the responses of plant phenology to climatic factors and to predict changes associated with future climate warming. The quality of these predictions depends critically on the quality of the underlying data. This study evaluates the representativeness and precision of data from the Swiss Phenology Network, which was implemented in 1951 by MeteoSwiss, and which currently includes 167 stations and 69 phenophases. The onset dates of these phenophases are recorded annually at each station by volunteering observers, leading to a data set with 186171 observations between 1951 and 2012. We analyse the spatial structure of phenological variation (considering mean onset dates through time, between-year variation and long-term trends), phenological responses to temperature through time and space, similarities in phenological time series between stations, and their use in predictive models for error detection. Results show that phenological variation across Switzerland is determined by altitude, large-scale spatial trends and local deviations (e.g. due to variation among individual plants and observation error), whereas small-scale spatial dependence (correlation of neighbouring stations) is weak. The number of stations currently included in the Swiss Phenology Network is sufficient for precise estimates of mean onset dates of each phenophase, of long-term trends and of responses to temperature for the entire country and for three altitudinal layers. More stations would be needed in some regions for a precise analysis of regional differences. The network does currently not include groups of stations with similar patterns of between-year variation for all phenological stages, i.e. no redundancy. A comparison of predictive models suggests that models with additive random effects of station and year (or station and year-specific temperature) are most suitable for data quality checking in practice. The inclusion of data from neighbouring stations, for other phenophases, or from the previous year hardly improves the detection of erroneous data entries. We conclude that the precision of results obtained from the Swiss Phenology Network depends more on the number of stations included in the network than on their exact geographic distribution as long as all regions are sufficiently represented. Given the important effect of altitude on phenological variation, the availability of phenological stations over a broad altitudinal range is a particular asset of the Swiss Phenology Network, which should be maintained.
	BibTeX: @REPORT{Gues:etal:18, AUTHOR = {Güsewell, S. and Pietragalla B, and Gehrig R, and Furrer, R. }, TITLE = {Representativeness of stations and reliability of data in the Swiss Phenology Network}, INSTITUTION = {Technical Report MeteoSwiss, 267}, YEAR = {2018}, URL = {http://www.meteoschweiz.admin.ch/content/dam/meteoswiss/it/Publikationen/doc/FB267_Guesewell_et_al.pdf}, PAGES = {100 pp}, DISPLAY = {Güsewell, S., Pietragalla, B., Gehrig, R. and Furrer, R. (2018). Representativeness of stations and reliability of data in the Swiss Phenology Network, Technical Report MeteoSwiss, 267, 100 pp.}, FUNDING = {URPP GCB}, }
	Brunner, M., Viviroli, D., Furrer, R., Seibert, J. and Favre Pugin, A.-C. (2018). Identification of Flood Reactivity Regions via the Functional Clustering of Hydrograph. Water Resources Research, 54(3), 1852–1867. [Abstract] [BibTeX]
	Abstract: Flood hydrograph shapes contain valuable information on the flood-generation mechanisms of a catchment. To make good use of this information, we express flood hydrograph shapes as continuous functions using a functional data approach. We propose a clustering approach based on functional data for flood hydrograph shapes to identify a set of representative hydrograph shapes on a catchment scale and use these catchment-specific sets of representative hydrographs to establish regions of catchments with similar flood reactivity on a regional scale. We applied this approach to flood samples of 163 medium-size Swiss catchments. The results indicate that three representative hydrograph shapes sufficiently describe the hydrograph shape variability within a catchment and therefore can be used as a proxy for the flood behavior of a catchment. These catchment-specific sets of three hydrographs were used to group the catchments into three reactivity regions of similar flood behavior. These regions were not only characterized by similar hydrograph shapes and reactivity but also by event magnitudes and triggering event conditions. We envision these regions to be useful in regionalization studies, regional flood frequency analyses, and to allow for the construction of synthetic design hydrographs in ungauged catchments. The clustering approach based on functional data which establishes these regions is very flexible and has the potential to be extended to other geographical regions or towards the use in climate impact studies. Keywords: Clustering, functional data analysis, hydrograph shapes, homogeneous regions, regionalization
	BibTeX: @ARTICLE{Brun:Vivi:Furr:etal:18, AUTHOR = {Manuela Brunner and Daniel Viviroli and Reinhard Furrer and Jan Seibert and Anne-Catherine Favre Pugin}, TITLE = {Identification of Flood Reactivity Regions via the Functional Clustering of Hydrograph}, JOURNAL = {Water Resour. Res.}, FJOURNAL = {Water Resources Research}, YEAR = {2018}, DOI = {10.1002/2017WR021650}, VOLUME = {54}, NUMBER = {3}, PAGES = {1852-1867}, FUNDING = {FOEN, MeteoSwiss, div.}, DISPLAY = {Brunner, M., Viviroli, D., Furrer, R., Seibert, J. and Favre Pugin, A.-C. (2018). Identification of Flood Reactivity Regions via the Functional Clustering of Hydrograph. Water Resources Research, 54(3), 1852-1867}, }
	Gerber, F., de Jong, R., Schaepman, M. E., Schaepman-Strub, G. and Furrer, R. (2018). Predicting Missing Values in Spatio-Temporal Remote Sensing Data. IEEE Transactions on Geoscience and Remote Sensing, 56(5), 2841–2853. [Abstract] [BibTeX]
	Abstract: Continuous, consistent, and long time-series from remote sensing are essential to monitoring changes on Earth's surface. However, analyzing such data sets is often challenging due to missing values introduced by cloud cover, missing orbits, sensor geometry artifacts, etc. We propose a new and accurate spatio-temporal prediction method to replace missing values in remote sensing data sets. The method exploits the spatial coherence and temporal seasonal regularity that are inherent in many data sets. The key parts of the method are (1) the adaptively-chosen spatio-temporal subsets around missing values, (2) the ranking of images within the subsets based on a scoring algorithm, (3) the estimation of empirical quantiles characterizing the missing values, and (4) the prediction of missing values though quantile regression. One advantage of quantile regression is the robustness to outliers, which enables more accurate parameter retrieval in the analysis of remote sensing data sets. In addition, we provide bootstrap-based quantification of prediction uncertainties. The proposed prediction method was applied to a Normalized Difference Vegetation Index (NDVI) data set from the Moderate Resolution Imaging Spectroradiometer (MODIS) and assessed with realistic test data sets featuring between 20% and 50% missing values. Validation against established methods showed that the proposed method has a good performance in terms of the root mean squared prediction error and significantly outperforms its competitors. The paper is accompanied by the open-source R package \pkg{gapfill}, which provides a flexible, fast, and ready-to-use implementation of the method. Keywords: Alaska, gap filling, imputation, interpolation, MODIS NDVI, quantile regression, R gapfill, TIMESAT, uncertainty.
	BibTeX: @ARTICLE{Gerb:etal:Furr:18, AUTHOR = {Florian Gerber and Rogier de~Jong and Michael E. Schaepman and Gabriela Schaepman--Strub and Reinhard Furrer}, TITLE = {Predicting Missing Values in Spatio-Temporal Remote Sensing Data}, JOURNAL = {IEEE Trans. Geosci. Remote Sens.}, FJOURNAL = {IEEE Transactions on Geoscience and Remote Sensing}, YEAR = {2018}, DOI = {10.1109/TGRS.2017.2785240}, VOLUME = {56}, NUMBER = {5}, PAGES = {2841--2853}, FUNDING = {URPP and more}, DISPLAY = {Gerber, F., de Jong, R., Schaepman, M. E., Schaepman-Strub, G. and Furrer, R. (2018). Predicting Missing Values in Spatio-Temporal Remote Sensing Data. IEEE Transactions on Geoscience and Remote Sensing, 56(5), 2841-2853.}, }
	Alegría, A., Porcu, E. and Furrer, R. (2018). Asymmetric Matrix-Valued Covariances for Multivariate Random Fields on Spheres, Journal of Statistical Computation and Simulation, 88(10), 1850–1862. [Abstract] [BibTeX]
	Abstract: Matrix-valued covariance functions are crucial to geostatistical modelling of multivariate spatial data. The classical assumption of symmetry of a multivariate covariance function is overly restrictive and has been considered as unrealistic for most of the real data applications. Despite of that, the literature on asymmetric covariance functions has been very sparse. In particular, there is some work related to asymmetric covariances on Euclidean spaces, depending on the Euclidean distance. However, for data collected over large portions of planet Earth, the most natural spatial domain is a sphere, with the corresponding geodesic distance being the natural metric. In this work, we propose a strategy based on spatial rotations to generate asymmetric covariances for multivariate random fields on the d-dimensional unit sphere. We illustrate through simulations as well as real data analysis that our proposal allows to achieve improvements in the predictive performance in comparison to the symmetric counterpart. Keywords: Cauchy model, geodesic distance, global data, rotation group, Wendland model.
	BibTeX: @ARTICLE{Aleg:Porc:Furr:18, AUTHOR = {Alegría, A and Porcu, E. and Furrer, R.}, TITLE = {Asymmetric matrix-valued covariances for multivariate random fields on spheres}, JOURNAL = {J. Stat. Comput. Simul.}, FJOURNAL = {Journal of Statistical Computation and Simulation}, YEAR = {2018}, DOI = {10.1080/00949655.2017.1406488}, VOLUME = {88}, NUMBER = {10}, PAGES = {1850--1862}, FUNDING = {SNF 143282 and more}, DISPLAY = {Alegría, A., Porcu, E. and Furrer, R. (2018). Asymmetric Matrix-Valued Covariances for Multivariate Random Fields on Spheres, Journal of Statistical Computation and Simulation, 88(10), 1850-1862.}, }
	Wang, C., Puhan, M. A., Furrer, R., for the SNC group (2018). Generalized Spatial Fusion Model Framework for Joint Analysis of Point and Areal Data. Spatial Statistics, 23, 72–90. [Abstract] [BibTeX]
	Abstract: The availability of geo-referenced data increased dramatically in recent years, motivating the use of spatial statistics in a variety of research fields, including epidemiology, environmental science, remote sensing, and economics. Combining data measured at both point and areal support can improve parameter estimation and increase prediction accuracy. We propose a new generalized spatial fusion model framework for jointly analyzing point and areal data. Assuming a common latent spatial process, we take a Bayesian hierarchical approach to model both types of data without distributional constraints. The models are implemented with nearest neighbor Gaussian process in Stan modeling language to increase computational efficiency and flexibility. Our simulation study shows that generalized fusion models under this framework model the latent process better than spatial process models. We identify scenarios where fusion models can offer large improvements. We then apply the framework to epidemiological data to identify the spatial risk pattern of respiratory diseases and lung cancer in Canton of Zurich, Switzerland. Keywords: Data fusion, Bayesian hierarchical model, Nearest neighbor Gaussian process, Change-of-support, Spatial epidemiology
	BibTeX: @ARTICLE{Wang:Puha:Furr:18, AUTHOR = {Craig Wang and Milo A. Puhan and Reinhard Furrer}, TITLE = {Generalized spatial fusion model framework for joint analysis of point and areal data}, JOURNAL = {Spat. Stat.}, FJOURNAL = {Spatial Statistics}, YEAR = {2018}, DOI = {10.1016/j.spasta.2017.11.006}, VOLUME = {23}, PAGES = {72--90}, FUNDING = {SNF 175529 and more}, DISPLAY = {Wang, C., Puhan, M. A., Furrer, R., for the SNC group (2018). Generalized Spatial Fusion Model Framework for Joint Analysis of Point and Areal Data. Spatial Statistics, 23, 72-90.}, }

2017

	Abiven, S., Altermatt, F., Backhaus, N., Deplazes-Zemp, A., Furrer, R., Korf, B., Niklaus, P. A., Schaepman-Strub, G., Shimizu, K. K., Zuppinger-Dingley, D., Petchey, O. L. and Schaepman, M. E. (2017). Integrative Research Efforts at the Boundary of Biodiversity and Global Change Research. Current Opinion in Environmental Sustainability, 29, 215–222. [Abstract] [BibTeX]
	Abstract: Global environmental change and biodiversity loss are closely linked through different feedback mechanisms. The University of Zurich Research Priority Programme on ‘Global Change and Biodiversity’ approach is to work with interdisciplinarity and transdisciplinarity to integrate mechanisms of interactions, feedback and scale and improve our understanding of the feedbacks between global change and biodiversity effects. Such work across research disciplines is not without its challenges. Here we share some of the questions that arose from our research approach over the last five years and how we addressed these challenges. First, our transdisciplinary approach allows combining different disciplines into a more holistic perspective towards integrative research, but demands collaborative work to establish common terminology, concepts, and metrics. Second, the research theme’s common perspective (biodiversity is desirable, global change is not) may also induce a confirmation bias from preconceived ideas. Third, new challenges emerge from scaling mechanisms and feedbacks at different spatial and temporal scales. Fourth, we investigate how to relate biodiversity, global change, ecosystem services and functions using interdisciplinary approaches. Fifth, we identify gaps between existing experiments and data requirements, and propose the definition of new experimental setups by linking processes and performing experiments at typical experimental scales as well as at larger scales. We conclude by emphasising the necessity to integrate theory, experiments, modelling and simulation, high performance computing and big data to understand feedbacks between biodiversity loss and processes of global change.
	BibTeX: @ARTICLE{Abiv:etal:17, AUTHOR = {Abiven, S., Altermatt, F., Backhaus, N., Deplazes-Zemp, A., Furrer, R., Korf, B., Niklaus, P. A., Schaepman-Strub, G., Shimizu, K. K., Zuppinger-Dingley, D., Petchey, O. L. and Schaepman, M. E.}, TITLE = {Integrative Research Efforts at the Boundary of Biodiversity and Global Change Research}, JOURNAL = {Curr. Opin. Environ. Sustainability}, FJOURNAL = {Current Opinion in Environmental Sustainability}, YEAR = {2017}, DOI = {10.1016/j.cosust.2018.04.016}, VOLUME = {29}, PAGES = {215--222}, FUNDING = {URPP-GCB}, DISPLAY = {Abiven, S., Altermatt, F., Backhaus, N., Deplazes-Zemp, A., Furrer, R., Korf, B., Niklaus, P. A., Schaepman-Strub, G., Shimizu, K. K., Zuppinger-Dingley, D., Petchey, O. L. and Schaepman, M. E. (2017). Integrative research efforts at the boundary of biodiversity and global change research. Current Opinion in Environmental Sustainability, 29, 215-222.}, }
	Farnham, A., Furrer, R., Blanke, U., Stone, E., Hatz, C. and Puhan, M. A. (2017). The quantified self during travel: mapping health in a prospective cohort of travellers. Journal of Travel Medicine, 24(5), tax050. [Abstract] [BibTeX]
	Abstract: Background: Travel medicine research has remained relatively unchanged in the face of rapid expansion of international travel and is unlikely to meet health challenges beyond infectious diseases. Our aim was to identify the range of health outcomes during travel using real-time monitoring and daily reporting of health behaviours and outcomes and identify traveller subgroups who may benefit from more targeted advice before and during travel. Methods: We recruited a prospective cohort of travellers ≥ 18 years and planning travel to Thailand for <5 weeks from the travel clinics in Zurich and Basel (Switzerland). Participants answered demographic, clinical and risk behaviour questionnaires pre-travel and a daily health questionnaire each day during travel using a smartphone application. Environmental and location data were collected passively by GPS. Classification trees were used to identify predictors of health behaviour and outcomes during travel. Results: Non-infectious disease events were relatively common, with 22.7% (17 out of 75 travellers) experiencing an accident, 40.0% (n = 30) a wound or cut and 14.7% (n = 11) a bite or lick from an animal. Mental health associated events were widely reported, with 80.0% (n = 60) reporting lethargy, 34.7% (n = 26) anxiety and 34.7% (n = 26) feeling tense or irritable. Classification trees identified age, trip length, previous travel experience and having experienced a sports injury in the past year as the most important discriminatory variables for health threats. Conclusions: Our study offers a revolutionary look at an almost real-time timeline of health events and behaviours during travel using mHealth technology. Non-infectious disease related health issues were common in this cohort, despite being largely unaddressed in traditional travel medicine research and suggest a substantial potential for improving evidence-based travel medicine advice. Keywords: mHealth, travel medicine, epidemiology, health behaviour.
	BibTeX: @ARTICLE{Farn:Furr:etal:17, AUTHOR = {Farnham, Andrea and Furrer, Reinhard and Blanke, Ulf and Stone, Emily and Hatz, Christoph and Puhan, Milo A.}, TITLE = {The quantified self during travel: mapping health in a prospective cohort of travellers}, JOURNAL = {J. Travel Med.}, FJOURNAL = {Journal of Travel Medicine}, YEAR = {2017}, DOI = {10.1093/jtm/tax050}, VOLUME = {24}, NUMBER = {5}, PAGES = {tax050}, FUNDING = {diverse}, DISPLAY = {Farnham, A., Furrer, R., Blanke, U., Stone, E., Hatz, C. and Puhan, M. A. (2017). The quantified self during travel: mapping health in a prospective cohort of travellers. Journal of Travel Medicine, 24(5), tax050.}, }
	Güsewell, S., Furrer, R. Gehrig, R. and Pietragalla, B. (2017). Changes in temperature sensitivity of spring phenology with recent climate warming in Switzerland are related to shifts of the preseason. Global Change Biology, 23(12), 5189–5202. [Abstract] [BibTeX]
	Abstract: The spring phenology of plants in temperate regions strongly responds to spring temperatures. Climate warming has caused substantial phenological advances in the past, but trends to be expected in the future are uncertain. A simple indicator is temperature sensitivity, the phenological advance statistically associated with a 1 °C warmer mean temperature during the ‘preseason’, defined as the most temperature-sensitive period preceding the phenological event. Recent analyses of phenological records have shown a decline in temperature sensitivity of leaf unfolding, but underlying mechanisms were not clear. Here we propose that climate warming can reduce temperature sensitivity simply by reducing the length of the preseason due to faster bud development during this time period, unless the entire preseason shifts forward so that its temperature does not change. We derive these predictions theoretically from the widely used ‘thermal time model’ for bud development and test them using data for 19 phenological events recorded in 1970–2012 at 108 stations spanning a 1600 m altitudinal range in Switzerland. We consider how temperature sensitivity, preseason start, preseason length and preseason temperature change (1) with altitude, (2) between the periods 1970–1987 and 1995–2012, which differed mainly in spring temperatures, and (3) between two non-consecutive sets of 18 years that differed mainly in winter temperatures. On average, temperature sensitivity increased with altitude (colder climate) and was reduced in years with warmer springs, but not in years with warmer winters. These trends also varied among species. Decreasing temperature sensitivity in warmer springs was associated with a limited forward shift of preseason start, higher temperatures during the preseason and reduced preseason length, but not with reduced winter chilling. Our results imply that declining temperature sensitivity can result directly from spring warming and does not necessarily indicate altered physiological responses or stronger constraints such as reduced winter chilling. Keywords: altitude, budburst, chilling, flowering, forcing, leaf unfolding, phenological network, thermal time model, time window model.
	BibTeX: @ARTICLE{Gues:Furr:etal:17, AUTHOR = {Sabine G\"usewell and Reinhard Furrer and Regula Gehrig and Barbara Pietragalla}, TITLE = {Changes in temperature sensitivity of spring phenology with recent climate warming in Switzerland are related to shifts of the preseason}, JOURNAL = {Glob. Chang. Biol.}, FJOURNAL = {Global Change Biology}, YEAR = {2017}, DOI = {10.1111/gcb.13781}, VOLUME = {23}, NUMBER = {12}, PAGES = {5189--5202}, FUNDING = {GCB, MeteoSwiss and more}, DISPLAY = {Güsewell, S., Furrer, R. Gehrig, R. and Pietragalla, B. (2017). Changes in temperature sensitivity of spring phenology with recent climate warming in Switzerland are related to shifts of the preseason. Global Change Biology, 23(12), 5189-5202.}, }
	Pittavino, M., Dreyfus, A., Heuer, C., Benschop, J., Wilson, P., Collins-Emerson, J., Torgerson, P. R. and Furrer, R. (2017). Comparison between Generalized Linear Modelling and Additive Bayesian Network; Identification of Factors associated with the Incidence of Antibodies against Leptospira interrogans sv Pomona in Meat Workers in New Zealand.. Acta Tropica, 173, 191-199. [Abstract] [BibTeX]
	Abstract: Background Additive Bayesian Network (ABN) is a graphical model which extends Generalized Linear Modelling (GLM) to multiple dependent variables. The present study compares results from GLM with those from ABN analysis used to identify factors associated with Leptospira interrogans sv Pomona (Pomona) infection by exploring the advantages and disadvantages of these two methodologies, to corroborate inferences informing health and safety measures at abattoirs in New Zealand (NZ). Methodology and findings In a cohort study in four sheep slaughtering abattoirs in NZ, sera were collected twice a year from 384 meat workers and tested by Microscopic Agglutination with a 91% sensitivity and 94% specificity for Pomona. The study primarily addressed the effect of work position, personal protective equipment (PPE) and non-work related exposures such as hunting on a new infection with Pomona. Significantly associated with Pomona were “Work position” and two “Abattoirs” (GLM), and “Work position” (ABN). The odds of Pomona infection (OR, [95% CI]) was highest at stunning and hide removal (ABN 41.0, [6.9–1044.2]; GLM 57.0, [6.9–473.3]), followed by removal of intestines, bladder, and kidneys (ABN 30.7, [4.9–788.4]; GLM 33.8, [4.2–271.1]). Wearing a facemask, glasses or gloves (PPE) did not result as a protective factor in GLM or ABN. Conclusions/Significance The odds of Pomona infection was highest at stunning and hide removal. PPE did not show any indication of being protective in GLM or ABN. In ABN all relationships between variables are modelled; hence it has an advantage over GLM due to its capacity to capture the natural complexity of data more effectively. Keywords: Leptospirosis; MCMC; R; JAGS; risk factors; protective equipment.
	BibTeX: @ARTICLE{Pitt:etal:Furr:17, AUTHOR = {M. Pittavino and A. Dreyfus and C. Heuer and J. Benschop and P. Wilson and J. Collins-Emerson and P. R. Torgerson and R. Furrer}, TITLE = {Comparison between Generalized Linear Modelling and Additive Bayesian Network; Identification of Factors associated with the Incidence of Antibodies against \emph{Leptospira interrogans} sv \emph{Pomona} in Meat Workers in New Zealand.}, JOURNAL = {Acta Trop.}, FJOURNAL = {Acta Tropica}, YEAR = {2017}, DOI = {10.1016/j.actatropica.2017.04.034}, VOLUME = {173}, NUMBER = {September}, PAGES = {191--199}, FUNDING = {SNSF138562, SNSF144973, PBBEBS-124186, data and more}, DISPLAY = {Pittavino, M., Dreyfus, A., Heuer, C., Benschop, J., Wilson, P., Collins-Emerson, J., Torgerson, P. R. and Furrer, R. (2017). Comparison between Generalized Linear Modelling and Additive Bayesian Network; Identification of Factors associated with the Incidence of Antibodies against Leptospira interrogans sv Pomona in Meat Workers in New Zealand. Acta Tropica, 173, 191-199.}, }
	Pittavino, M., Dreyfus, A., Heuer, C., Benschop, J., Wilson, P., Collins-Emerson, J., Torgerson, P. R. and Furrer, R. (2017). Data on Leptospira interrogans sv Pomona in Meat Workers in New Zealand. Data in Brief, 13, 587-596. [Abstract] [BibTeX]
	Abstract: The data presented in this article are related to the research article entitled “Comparison between Generalized Linear Modelling and Additive Bayesian Network; Identification of Factors associated with the Incidence of Antibodies against Leptospira interrogans sv Pomona in Meat Workers in New Zealand” (Pittavino et al., 2017). A prospective cohort study was conducted in four sheep slaughtering abattoirs in New Zealand (NZ) (Dreyfus et al., 2015). Sera were collected twice a year from 384 meat workers and tested by Microscopic Agglutination for Leptospira interrogans sv Pomona (Pomona) infection, one of the most common Leptospira serovars in humans in NZ. This article provides an extended analysis of the data, illustrating the different steps of a multivariable (i.e. generalized linear model) and especially a multivariate tool based on additive Bayesian networks (ABN) modelling. Keywords: Leptospirosis; Interviews; Bayesian networks; Markov chain Monte Carlo; Bootstrapping
	BibTeX: @ARTICLE{Pitt:etal:Furr:17, AUTHOR = {M. Pittavino and A. Dreyfus and C. Heuer and J. Benschop and P. Wilson and J. Collins-Emerson and P. R. Torgerson and R. Furrer}, TITLE = {Data on \emph{Leptospira interrogans} sv \emph{Pomona} in Meat Workers in New Zealand.}, JOURNAL = {Data in Brief}, FJOURNAL = {Data in Brief}, YEAR = {2017}, DOI = {10.1016/j.dib.2017.05.053}, VOLUME = {13}, NUMBER = {August}, PAGES = {587--596}, FUNDING = {SNSF138562, SNSF144973, PBBEBS-124186, data and more}, DISPLAY = {Pittavino, M., Dreyfus, A., Heuer, C., Benschop, J., Wilson, P., Collins-Emerson, J., Torgerson, P. R. and Furrer, R. (2017). Data on Leptospira interrogans sv Pomona in Meat Workers in New Zealand. Data in Brief, 13, 587-596.}, }
	Gerber, F., Mösinger, K., and Furrer, R. (2017). Extending R Packages to Support 64-bit Compiled Code: An Illustration with spam64 and GIMMS NDVI_3g Data. Computers & Geosciences, 104, 109-119. [Abstract] [BibTeX]
	Abstract: Software packages for spatial data often implement a hybrid approach of interpreted and compiled programming languages. The compiled parts are usually written in C, C++, or Fortran, and are efficient in terms of computational speed and memory usage. Conversely, the interpreted part serves as a convenient user-interface and calls the compiled code for computationally demanding operations. The price paid for the user friendliness of the interpreted component is—besides performance—the limited access to low level and optimized code. An example of such a restriction is the 64-bit vector support of the widely used statistical language R. On the R side, users do not need to change existing code and may not even notice the extension. On the other hand, interfacing 64-bit compiled code efficiently is challenging. Since many R packages for spatial data could benefit from 64-bit vectors, we investigate strategies to efficiently pass 64-bit vectors to compiled languages. More precisely, we show how to simply extend existing R packages using the foreign function interface to seamlessly support 64-bit vectors. This extension is shown with the sparse matrix algebra R package spamspam. The new capabilities are illustrated with an example of GIMMS NDVI3g data featuring a parametric modeling approach for a non-stationary covariance matrix. Keywords: Sparse matrix; Non-stationarity; Compactly supported covariance function; Huge dataset; dotCall64; Foreign function interface
	BibTeX: @ARTICLE{Gerb:Moes:Furr:17, AUTHOR = {Florian Gerber and Kaspar M\"osinger and Reinhard Furrer}, TITLE = {Extending R Packages to Support 64-bit Compiled Code: An Illustration with spam64 and {GIMMS} {NDVI}\textsubscript{3g} Data}, JOURNAL = {Comput. Geosci.}, FJOURNAL = {Computers \& Geosciences}, YEAR = {2017}, DOI = {10.1016/j.cageo.2016.11.015}, VOLUME = {104}, PAGES = {109--119}, FUNDING = {URPP GCB, data}, DISPLAY = {Gerber, F., Mösinger, K., and Furrer, R. (2017). Extending R Packages to Support 64-bit Compiled Code: An Illustration with spam64 and GIMMS NDVI3g Data. Computers & Geosciences, 104, 109-119}, }
	Wang, C., Torgerson, P. R., Höglund, J. and Furrer, R. (2017). Zero-inflated hierarchical models for faecal egg counts to assess anthelmintic efficacy. Veterinary Parasitology, 235, 20–28. [Abstract] [BibTeX]
	Abstract: The prevalence of anthelmintic resistance has increased in recent years, as a result of the extensive use of anthelmintic drugs to reduce the infection of parasitic worms in livestock. In order to detect the resistance, the number of parasite eggs in animal faeces is counted. Typically a subsample of the diluted faeces is examined, and the mean egg counts from both untreated and treated animals are compared. However, the conventional method ignores the variabilities introduced by the counting process and by different infection levels across animals. In addition, there can be extra zero counts, which arise as a result of the unexposed animals in an infected population or animals. In this paper, we propose the zero-inflated Bayesian hierarchical models to estimate the reduction in faecal egg counts. The simulation study compares the Bayesian models with the conventional faecal egg count reduction test and other methods such as bootstrap and quasi-Poisson regression. The results show the Bayesian models are more robust and they perform well in terms of both the bias and the coverage. We further illustrate the advantages of our proposed model using a case study about the anthelmintic resistance in Swedish sheep flocks. Keywords: Bayesian hierarchical model; Faecal egg count reduction test; Anthelmintic resistance; Zero-inflated models; Statistical analysis
	BibTeX: @ARTICLE{Furr::17, AUTHOR = {Craig Wang and Paul R. Torgerson and Johan Höglund and Reinhard Furrer}, TITLE = {Zero-inflated hierarchical models for faecal egg counts to assess anthelmintic efficacy}, JOURNAL = {Vet. Parasitol.}, FJOURNAL = {Veterinary Parasitology}, YEAR = {2017}, DOI = {10.1016/j.vetpar.2016.12.007}, VOLUME = {235}, PAGES = {20--28}, FUNDING = {SNSF-144973}, DISPLAY = {Wang, C., Torgerson, P. R., Höglund, J. and Furrer, R. (2017). Zero-inflated hierarchical models for faecal egg counts to assess anthelmintic efficacy. Veterinary Parasitology, 235, 20–28.}, }

2016

	van der Lely, S., Stefanovic, M., Schmidhalter, M. R., Pittavino, M., Furrer, R., Liechti, M. D., Schubert, M., Kessler T. M. and Mehnert U. (2017). Protocol for a prospective, randomized study on neurophysiological assessment of lower urinary tract function in a healthy cohort. BMC Urology, 16:69. [Abstract] [BibTeX]
	Background: Lower urinary tract symptoms are highly prevalent and a large proportion of these symptoms are known to be associated with a dysfunction of the afferent pathways. Diagnostic tools for an objective and reproducible assessment of afferent nerve function of the lower urinary tract are missing. Previous studies showed first feasibility results of sensory evoked potential recordings following electrical stimulation of the lower urinary tract in healthy subjects and patients. Nevertheless, a refinement of the methodology is necessary. Keywords: Sensory evoked potential Electroencephalography Lower urinary tract Urinary bladder Urethra Randomized Lower urinary tract dysfunction Current perception threshold A-delta afferent fibers Electrical stimulation
	BibTeX: @ARTICLE{vdLe:etal:16, AUTHOR = {Stéphanie van der Lely and Martina Stefanovic and Melanie R. Schmidhalter and Marta Pittavino and Reinhard Furrer and Martina D. Liechti and Martin Schubert and Thomas M. Kessler and Ulrich Mehnert}, TITLE = {Protocol for a prospective, randomized study on neurophysiological assessment of lower urinary tract function in a healthy cohort}, JOURNAL = {BMC Urology}, FJOURNAL = {BMC Urology}, YEAR = {2016}, DOI = {10.1186/s12894-016-0188-9}, VOLUME = {16}, NUMBER = {1}, PAGES = {69}, FUNDING = {div}, DISPLAY = {van der Lely, S., Stefanovic, M., Schmidhalter, M. R., Pittavino, M., Furrer, R., Liechti, M. D., Schubert, M., Kessler T. M. and Mehnert U. (2017). Protocol for a prospective, randomized study on neurophysiological assessment of lower urinary tract function in a healthy cohort. BMC Urology, 16:69.}, }
	Furrer, R., Bachoc, F. and Du, J. (2016). Asymptotic Properties of Multivariate Tapering for Estimation and Prediction. Journal of Multivariate Analysis, 149, 177–191. [Abstract] [BibTeX]
	Abstract: Parameter estimation for and prediction of spatially or spatio-temporally correlated random processes are used in many areas and often require the solution of a large linear system based on the covariance matrix of the observations. In recent years, the dataset sizes to which these methods are applied have steadily increased such that straightforward statistical tools are computationally too expensive to be used. In the univariate context, tapering, i.e., creating sparse approximate linear systems, has been shown to be an efficient tool in both the estimation and prediction settings. The asymptotic properties are derived under an infill asymptotic setting. In this paper we use a domain increasing framework for estimation and prediction using multivariate tapering. Under this asymptotic regime we prove that tapering (one-tapered form) preserves the consistency of the untapered maximum likelihood estimator and show that tapering has asymptotically the same mean squared prediction error as using the corresponding untapered predictor. The theoretical results are illustrated with simulations. Keywords: One-taper likelihood; Gaussian random field; Domain increasing; Sparse matrix
	BibTeX: @ARTICLE{Furr:Bach:Du:16, AUTHOR = {Reinhard Furrer and François Bachoc and Juan Du}, TITLE = {Asymptotic Properties of Multivariate Tapering for Estimation and Prediction}, JOURNAL = {J. Multivariate Anal.}, FJOURNAL = {Journal of Multivariate Analysis}, YEAR = {2016}, DOI = {10.1016/j.jmva.2016.04.006}, VOLUME = {149}, PAGES = {177--191}, FUNDING = {GCB, SNSF-143282}, DISPLAY = {Furrer, R., Bachoc, F. and Du, J. (2016). Asymptotic Properties of Multivariate Tapering for Estimation and Prediction. Journal of Multivariate Analysis, 149, 177–191.}, }
	Bachoc, F. and Furrer, R. (2016). On the smallest eigenvalues of covariance matrices of multivariate spatial processes. STAT, 5(1), 102–107. [Abstract] [BibTeX]
	Abstract: There has been a growing interest in providing models for multivariate spatial processes. A majority of these models specify a parametric matrix covariance function. Based on observations, the parameters are estimated by maximum likelihood or variants thereof. While the asymptotic properties of maximum likelihood estimators for univariate spatial processes have been analyzed in detail, maximum likelihood estimators for multivariate spatial processes have not received their deserved attention yet. In this article, we consider the classical increasing-domain asymptotic setting restricting the minimum distance between the locations. Then, one of the main components to be studied from a theoretical point of view is the asymptotic positive definiteness of the underlying covariance matrix. Based on very weak assumptions on the matrix covariance function, we show that the smallest eigenvalue of the covariance matrix is asymptotically bounded away from zero. Several practical implications are discussed as well. Keywords: increasing-domain asymptotics; matrix covariance function; maximum likelihood; multivariate process; spectral representation; spectrum
	BibTeX: @ARTICLE{Bach:Furr:16, AUTHOR = {François Bachoc and Reinhard Furrer}, TITLE = {On the smallest eigenvalues of covariance matrices of multivariate spatial processes}, JOURNAL = {STAT}, FJOURNAL = {STAT}, YEAR = {2016}, DOI = {10.1002/sta4.107}, VOLUME = {5}, NUMBER = {1}, PAGES = {102--107}, FUNDING = {GCB, SNSF-143282}, DISPLAY = {Bachoc, F., and Furrer, R. (2016). On the smallest eigenvalues of covariance matrices of multivariate spatial processes. STAT, 5(1), 102–107.} }
	Addor, N., Rohrer, M., Furrer, R. and Seibert, J. (2016). Propagation of biases in climate models from the synoptic to the regional scale: Implications for bias adjustment. Journal of Geophysical Research: Atmospheres, 121(5), 2075–2089. [Abstract] [BibTeX]
	Abstract: Bias adjustment methods usually do not account for the origins of biases in climate models and instead perform empirical adjustments. Biases in the synoptic circulation are for instance often overlooked when postprocessing regional climate model (RCM) simulations driven by general circulation models (GCMs). Yet considering atmospheric circulation helps to establish links between the synoptic and the regional scale, and thereby provides insights into the physical processes leading to RCM biases. Here we investigate how synoptic circulation biases impact regional climate simulations and influence our ability to mitigate biases in precipitation and temperature using quantile mapping. We considered 20 GCM-RCM combinations from the ENSEMBLES project and characterized the dominant atmospheric flow over the Alpine domain using circulation types. We report in particular a systematic overestimation of the frequency of westerly flow in winter. We show that it contributes to the generalized overestimation of winter precipitation over Switzerland, and this wet regional bias can be reduced by improving the simulation of synoptic circulation. We also demonstrate that statistical bias adjustment relying on quantile mapping is sensitive to circulation biases, which leads to residual errors in the postprocessed time series. Overall, decomposing GCM-RCM time series using circulation types reveals connections missed by analyses relying on monthly or seasonal values. Our results underscore the necessity to better diagnose process misrepresentation in climate models to progress with bias adjustment and impact modeling. Keywords: bias adjustment; regional climate simulation; impact modeling; synoptic circulation; downscaling; process misrepresentation
	BibTeX: @ARTICLE{Furr::16, AUTHOR = {Nans Addor and Marco Rohrer and Reinhard Furrer and Jan Seibert}, TITLE = {Propagation of biases in climate models from the synoptic to the regional scale: Implications for bias adjustment}, JOURNAL = {J. Geophys. Res. Atmos.}, FJOURNAL = {Journal of Geophysical Research: Atmospheres}, YEAR = {2016}, DOI = {10.1002/2015JD024040}, VOLUME = {121}, NUMBER = {5}, PAGES = {2075--2089}, FUNDING = {URPP GCB; 200021_131995}, DISPLAY = {Addor, N., Rohrer, M., Furrer, R. and Seibert, J. (2016). Propagation of biases in climate models from the synoptic to the regional scale: Implications for bias adjustment. J. Geophys. Res. Atmos., 121(5), 2075–2089, doi:10.1002/2015JD024040.}, }
	Hombach, M., Ochoa, C., Maurer, F. P., Pfiffner, T., Böttger, E. C. and Furrer, R. (2016). Relative contribution of biological variation and technical variables to zone diameter variations of disc diffusion susceptibility testing. Journal of Antimicrobial Chemotherapy, 71(1), 141–151. [Abstract] [BibTeX]
	Abstract: Objectives Disc diffusion is still largely based on manual procedures. Technical variations originate from inoculum preparation, variations in materials, individual operator plate streaking and reading accuracy. Resulting measurement imprecision contributes to categorization errors. Biological variation resembles the natural fluctuation of a measured parameter such as antibiotic susceptibility around a mean value. It is deemed to originate from factors such as genetic background or metabolic state. This study analysed the relative contribution of different technical and biological factors to total disc diffusion variation. Methods For calculation of relative error factor contribution to disc diffusion variability, five experiments were designed keeping different combinations of error factors constant. A mathematical model was developed to analyse the individual error factor contribution to disc diffusion variation for each of the tested drug-species combinations. Results The contribution of biological variation to total diameter variance ranged from 10.4% to 98.8% for different drug?species combinations. Highest biological variation was found for Enterococcus faecalis WT and vancomycin (98.8%) and for penicillinase-producing Staphylococcus aureus and penicillin G (96.0%). Average imprecision of automated zone reading revealed that 1.4%-5.3% of total imprecision was due to technical variation, while materials, i.e. antibiotic discs and agar plates, contributed between 2.6% and 3.9%. Inoculum preparation and manual plate streaking contributed 6.8%-24.8% and 6.6%-24.3%, respectively, to total imprecision. Conclusions This study illustrates the relative contributions of technical factors that account for a significant part of total variance in disc diffusion. The highest relative contribution originated from the operator, i.e. manual inoculum preparation and plate streaking. Further standardization of inoculum preparation and plate streaking by automation could potentially increase the precision of disc diffusion and improve the correlation of susceptibility reports with clinical outcome.
	BibTeX: @ARTICLE{Homb:etal:16, AUTHOR = {Hombach, M. and Ochoa, C. and Maurer, F. P. and Pfiffner, T. and Böttger, E. C. and Furrer, R.}, TITLE = {Relative contribution of biological variation and technical variables to zone diameter variations of disc diffusion susceptibility testing}, JOURNAL = {J. Antimicrob. Chemother.}, FJOURNAL = {Journal of Antimicrobial Chemotherapy}, YEAR = {2016}, DOI = {10.1093/jac/dkv309}, VOLUME = {71}, NUMBER = {1}, PAGES = {141--151}, DISPLAY = {Hombach, M., Ochoa, C., Maurer, F. P., Pfiffner, T., Böttger, E. C. and Furrer, R. (2016). Relative contribution of biological variation and technical variables to zone diameter variations of disc diffusion susceptibility testing. Journal of Antimicrobial Chemotherapy, 71(1), 141–151.}, }

2015

	Leiterer, R. and Torabzadeh, H. and Furrer, R. and Schaepman, M. E. and Morsdorf, F. (2015). Towards Automated Characterization of Canopy Layering in Mixed Temperate Forests Using Airborne Laser Scanning. Forests, 6(11), 4146–4167. [Abstract] [BibTeX]
	Abstract: Canopy layers form essential structural components, affecting stand productivity and wildlife habitats. Airborne laser scanning (ALS) provides horizontal and vertical information on canopy structure simultaneously. Existing approaches to assess canopy layering often require prior information about stand characteristics or rely on pre-defined height thresholds. We developed a multi-scale method using ALS data with point densities >10 pts/m2 to determine the number and vertical extent of canopy layers (canopylayer, canopylength), seasonal variations in the topmost canopy layer (canopytype), as well as small-scale heterogeneities in the canopy (canopyheterogeneity). We first tested and developed the method on a small forest patch (800 ha) and afterwards tested transferability and robustness of the method on a larger patch (180,000 ha). We validated the approach using an extensive set of ground data, achieving overall accuracies >77% for canopytype and canopyheterogeneity, and >62% for canopylayer and canopylength. We conclude that our method provides a robust characterization of canopy layering supporting automated canopy structure monitoring. Keywords: remote sensing; multi-scale; operational; point cloud; area-based approach; forest inventory; vegetation structure; LiDAR
	BibTeX: @ARTICLE{Leit:etal:15, AUTHOR = {Leiterer, Reik and Torabzadeh, Hossein and Furrer, Reinhard and Schaepman, Michael E. and Morsdorf, Felix}, TITLE = {Towards Automated Characterization of Canopy Layering in Mixed Temperate Forests Using Airborne Laser Scanning}, JOURNAL = {Forests}, FJOURNAL = {Forests}, YEAR = {2015}, DOI = {10.3390/f6114146}, VOLUME = {6}, NUMBER = {11}, PAGES = {4146--4167}, DISPLAY = {Leiterer, R. and Torabzadeh, H. and Furrer, R. and Schaepman, M. E. and Morsdorf, F. (2015). Towards Automated Characterization of Canopy Layering in Mixed Temperate Forests Using Airborne Laser Scanning. Forests, 6(11), 4146–4167.}, }
	Hombach, M., Maurer, F. P., Pfiffner, T., Böttger, E. C. and Furrer, R. (2015). Standardization of operator-dependent variables affecting precision and accuracy of the disk diffusion method for antibiotic susceptibility testing. Journal of Clinical Microbiology, 53(12), 3864–3869. [Abstract] [BibTeX]
	Abstract: Parameters like zone reading, inoculum density, and plate streaking influence the precision and accuracy of disk diffusion antibiotic susceptibility testing (AST). While improved reading precision has been demonstrated using automated imaging systems, standardization of the inoculum and of plate streaking have not been systematically investigated yet. This study analyzed whether photometrically controlled inoculum preparation and/or automated inoculation could further improve the standardization of disk diffusion. Suspensions of Escherichia coli ATCC 25922 and Staphylococcus aureus ATCC 29213 of 0.5 McFarland standard were prepared by 10 operators using both visual comparison to turbidity standards and a Densichek photometer (bioMérieux), and the resulting CFU counts were determined. Furthermore, eight experienced operators each inoculated 10 Mueller-Hinton agar plates using a single 0.5 McFarland standard bacterial suspension of E. coli ATCC 25922 using regular cotton swabs, dry flocked swabs (Copan, Brescia, Italy), or an automated streaking device (BD-Kiestra, Drachten, Netherlands). The mean CFU counts obtained from 0.5 McFarland standard E. coli ATCC 25922 suspensions were significantly different for suspensions prepared by eye and by Densichek (P < 0.001). Preparation by eye resulted in counts that were closer to the CLSI/EUCAST target of 108 CFU/ml than those resulting from Densichek preparation. No significant differences in the standard deviations of the CFU counts were observed. The interoperator differences in standard deviations when dry flocked swabs were used decreased significantly compared to the differences when regular cotton swabs were used, whereas the mean of the standard deviations of all operators together was not significantly altered. In contrast, automated streaking significantly reduced both interoperator differences, i.e., the individual standard deviations, compared to the standard deviations for the manual method, and the mean of the standard deviations of all operators together, i.e., total methodological variation.
	BibTeX: @ARTICLE{Homb:etal:15, AUTHOR = {Hombach, M. and Maurer, F. P. and Pfiffner, T. and Böttger, E. C. and Furrer, R.}, TITLE = {Standardization of operator-dependent variables affecting precision and accuracy of the disk diffusion method for antibiotic susceptibility testing}, JOURNAL = {J. Clin. Microbiol.}, FJOURNAL = {Journal of Clinical Microbiology}, YEAR = {2016}, DOI = {10.1128/JCM.02351-15}, VOLUME = {53}, NUMBER = {12}, PAGES = {3864--3869}, DISPLAY = {Hombach, M., Maurer, F. P., Pfiffner, T., Böttger, E. C. and Furrer, R. (2015). Standardization of operator-dependent variables affecting precision and accuracy of the disk diffusion method for antibiotic susceptibility testing. Journal of Clinical Microbiology, 53(12), 3864–3869.}, }
	Leiterer, R., Furrer, R., Schaepman, M. E. and Morsdorf, F. (2015). Forest canopy-structure characterization: A data-driven approach. Forest Ecology and Management, 358, 48–61. [Abstract] [BibTeX]
	Abstract: Forest canopy structure influences and partitions the energy fluxes between the atmosphere and vegetation. It serves as an indicator of a variety of biophysical variables and ecosystem goods and services. Airborne laser scanning (ALS) can simultaneously provide horizontal and vertical information on canopy structure. Existing approaches to assess canopy structure often focus on in situ collected structural variables and require a substantial set of prior information about stand characteristics. They also rely on pre-defined spatial units and are usually dependent on site-specific model calibrations. We propose a method to provide quantitative canopy-structure descriptors on different scales, retrieved from ALS data. The approach includes (i) a sensitivity assessment and a quantification of ALS-derived canopy-structure information dependent on ALS data properties, (ii) an automatic determination of the most feasible spatial unit for canopy-structure characterization, and (iii) the derivation of canopy-structure types (CSTs) using a hierarchical, multi-scale classification approach based on Bayesian robust mixture models (BRMM), satisfying structurally homogenous criteria without the use of in situ calibration information. The CSTs resulted in retrievals of canopy layering (single-, two-, and multi-layered canopies) and canopy types (deciduous or evergreen canopies). Retrievals classified seven CSTs with accuracies ranging from 52% to 82% user accuracy (canopy layering) and 89-99% user accuracy (canopy type). The method supports a data-driven approach, allowing for an efficient monitoring of canopy structure. Keywords: LiDAR; ALS; Remote sensing; Multi-scale; Functional diversity; Vegetation
	BibTeX: @ARTICLE{Leit:Furr:etal:15, AUTHOR = {Reik Leiterer and Reinhard Furrer and Michael E. Schaepman and Felix Morsdorf}, TITLE = {Forest canopy-structure characterization: A data-driven approach}, JOURNAL = {}, FJOURNAL = {Forest Ecology and Management}, YEAR = {2015}, DOI = {10.1016/j.foreco.2015.09.003}, VOLUME = {358}, NUMBER = {}, PAGES = {48--61}, DISPLAY = {Leiterer, R., Furrer, R., Schaepman, M. E. and Morsdorf, F. (2015). Forest canopy-structure characterization: A data-driven approach. Forest Ecology and Management, 358, 48–61.}, }
	Baggiolini, A., Varum, S., Mateos J. M., Bettosini, D., John, N., Bonalli, M., Ziegler, U., Dimou, L., Clevers, H., Furrer, R., and Sommer, L. (2015). Premigratory and Migratory Neural Crest Cells Are Multipotent In Vivo, Cell Stem Cell, 16(3), 314–322. See also Preview Confetti Clarifies Controversy: Neural Crest Stem Cells Are Multipotent by M. Bronner (dx:10.1016/j.stem.2015.02.016). [Abstract] [BibTeX]
	Abstract: The neural crest (NC) is an embryonic stem/progenitor cell population that generates a diverse array of cell lineages, including peripheral neurons, myelinating Schwann cells, and melanocytes, among others. However, there is a long-standing controversy as to whether this broad developmental perspective reflects in vivo multipotency of individual NC cells or whether the NC is comprised of a heterogeneous mixture of lineage-restricted progenitors. Here, we resolve this controversy by performing in vivo fate mapping of single trunk NC cells both at premigratory and migratory stages using the R26R-Confetti mouse model. By combining quantitative clonal analyses with definitive markers of differentiation, we demonstrate that the vast majority of individual NC cells are multipotent, with only few clones contributing to single derivatives. Intriguingly, multipotency is maintained in migratory NC cells. Thus, our findings provide definitive evidence for the in vivo multipotency of both premigratory and migrating NC cells in the mouse.
	BibTeX: @ARTICLE{Bagg:etal:15, AUTHOR = {Arianna Baggiolini and Sandra Varum and Jos\'e Mar\'\i a Mateos and Damiano Bettosini and Nessy John and Mario Bonalli and Urs Ziegler and Leda Dimou and Hans Clevers and Reinhard Furrer and Lukas Sommer}, TITLE = {Premigratory and Migratory Neural Crest Cells Are Multipotent In Vivo}, JOURNAL = {Cell Stem Cell}, FJOURNAL = {Cell Stem Cell}, YEAR = {2015}, DOI = {10.1016/j.stem.2015.02.017}, VOLUME = {16}, NUMBER = {3}, PAGES = {314--322}, FUNDING = {NRP-63; URPP TCR; URPP SB/FG}, DISPLAY = {Baggiolini, A., Varum, S., Mateos J. M., Bettosini, D., John, N., Bonalli, M., Ziegler, U., Dimou, L., Clevers, H., Furrer, R., and Sommer, L. (2015). Premigratory and Migratory Neural Crest Cells Are Multipotent In Vivo, Cell Stem Cell, 16(3), 314–322.}, }
	Gerber, F. and Furrer, R. (2015). Pitfalls in the implementation of Bayesian hierarchical modeling of areal count data: An illustration using BYM and Leroux models. Journal of Statistical Software, Code Snippets, 63(1), 1–32. [Abstract] [BibTeX]
	Abstract: Several different hierarchical Bayesian models can be used for the estimation of spatial risk patterns based on spatially aggregated count data. Typically, the resulting posterior distributions of the model parameters cannot be expressed in closed forms, and MCMC approaches are required for inference. However, implementations of hierarchical Bayesian models for such areal data are error-prone. Also, different implementation methods exist, and a surprisingly large variability may develop between the methods as well as between the different MCMC runs of one method. This paper has four main goals: (1) to present a point by point annotated code of two commonly used models for areal count data, namely the BYM and the Leroux models (2) to discuss technical variations in the implementation of a formula-driven sampler and to assess the variability in the posterior results from various alternative implementations (3) to give graphical tools to compare sample(r)s which complement existing convergence diagnostics and (4) to give various practical tips for implementing samplers. KEYWORDS: MCMC, GMRF, INLA, R, openBUGS, geoBUGS, spam, CARBayes
	BibTeX: @ARTICLE{Gerb:Furr:15, AUTHOR = {Gerber, F. and Furrer, R.}, TITLE = {Pitfalls in the implementation of {Bayesian} hierarchical modeling of areal count data: An illustration using {BYM} and {Leroux} models}, JOURNAL = {J. Stat. Softw.}, FJOURNAL = {Journal of Statistical Software, Code Snippets}, YEAR = {2015}, DOI = {10.18637/jss.v063.c01}, URL = {http://www.jstatsoft.org/v63/c01/}, VOLUME = {63}, NUMBER = {1}, PAGES = {1--32}, FUNDING = {URPP GCB; SNSF 143282, 144973}, DISPLAY = {Gerber, F. and Furrer, R. (2015). Pitfalls in the implementation of Bayesian hierarchical modeling of areal count data: An illustration using BYM and Leroux models. Journal of Statistical Software, Code Snippets, 63(1), 1–32.}, }
	Geinitz, S., Furrer, R. and Sain, S. R. (2015). Bayesian multilevel analysis of variance for relative comparison across sources of global climate model variability. International Journal of Climatology, 35(3), 433–443. [Abstract] [BibTeX]
	Abstract: Projections of future climate conditions are carried out by many research institutions, each with their own general circulation model to do so. The projections are additionally subjected to distinct anthropogenic forcings, specified by future greenhouse gas emissions scenarios. These two factors, together with their temporal effects and interaction, create several potential sources of variation in final climate projection output. Multilevel statistical models, and specifically multilevel ANOVA, have come to be widely used for many reasons, not least of which is their ability to comprehensively assess many different sources of variation. In this article, a Bayesian multilevel ANOVA approach is applied to climate projections to assess each of these sources of variation, estimate the uncertainty regarding the assessment, and to allow comparison across all sources. The data originate from phase three of the Coupled Model Intercomparison Project (CMIP3), consisting of 11 circulation models and three emissions scenarios over nine decadal time periods for boreal summer and winter. Data from the next phase, CMIP5, is now becoming available. As this approach towards ANOVA is relatively novel, and particularly so for spatial data, a short discussion of conventional ANOVA and the new methodology is provided. KEYWORDS: climate change; uncertainty; variance components
	BibTeX: @ARTICLE{Gein:Furr:Sain:15, AUTHOR = {Geinitz, S. and Furrer, R. and Sain, S. R.}, TITLE = {Bayesian multilevel analysis of variance for relative comparison across sources of global climate model variability}, JOURNAL = {Int. J. Climatol.}, FJOURNAL = {International Journal of Climatology}, YEAR = {2015}, DOI = {10.1002/joc.3991}, VOLUME = {35}, NUMBER = {3}, PAGES = {433--443}, FUNDING = {SNSF 143282; URPP GCB}, DISPLAY = {Geinitz, S., Furrer, R. and Sain, S. R. (2015). Bayesian multilevel analysis of variance for relative comparison across sources of global climate model variability. International Journal of Climatology, 35(3), 433–443.}, }

2014

Torgerson, P. R., Paul, M. and Furrer, R. (2014). Evaluating faecal egg count reduction using a specifically designed package "eggCounts" in R and a user friendly web interface. International Journal for Parasitology, 44(5), 299–303. [Abstract] [BibTeX]

Abstract: The seemingly straightforward task of analysing faecal egg counts resulting from laboratory procedures such as the McMaster technique has, in reality, a number of complexities. These include Poisson errors in the counting technique which result from eggs being randomly distributed in well mixed faecal samples. In addition, counts between animals in a single experimental or observational group are nearly always over-dispersed. We describe the R package “eggCounts” that we have developed that incorporates both sampling error and over-dispersion between animals to calculate the true egg counts in samples of faeces, the probability distribution of the true counts and summary statistics such as the 95% uncertainty intervals. Based on a hierarchical Bayesian framework, the software will also rigorously estimate the percentage reduction of faecal egg counts and the 95% uncertainty intervals of data generated by a faecal egg count reduction test. We have also developed a user friendly web interface that can be used by those with limited knowledge of the R statistical computing environment. We illustrate the package with three simulated data sets of faecal egg count reduction experiments.

KEYWORDS: Faecal egg count reduction test; Anthelmintic resistance; Mathematical techniques; Statistical analysis; Bayesian hierarchical model

BibTeX:

@ARTICLE{Torg:Paul:Furr:14,
  AUTHOR = 	 {Torgerson, P. R. and Paul, M. and Furrer, R.},
  TITLE = 	 {Evaluating faecal egg count reduction using a specifically designed package "eggCounts" in R and a user friendly web interface},
  JOURNAL = 	 {Int. J. Parasitol.},
  FJOURNAL = 	 {International Journal of Parasitology},
  YEAR = 	 {2014},
  DOI =          {10.1016/j.ijpara.2014.01.005},
  PMID =         {24556564}, 
  VOLUME = 	 {44},
  NUMBER = 	 {5},
  PAGES = 	 {299--303},
  DISPLAY =      {Torgerson, P. R., Paul, M. and Furrer, R. (2014). Evaluating faecal egg count reduction using a specifically designed package "eggCounts" in R and a user friendly web interface. International Journal for Parasitology, 44(5), 299–303.},
}

Wuest, S. L., Richard, S., Walther, I., Furrer, R., Anderegg, R., Sekler, J. and Egli, M. (2014). A Novel Microgravity Simulator Applicable for Three-Dimensional Cell Culturing. Microgravity Science and Technology, 26(2), 77–88. [Abstract] [BibTeX]

Abstract:Random Positioning Machines (RPM) were introduced decades ago to simulate microgravity. Since then numerous experiments have been carried out to study its influence on biological samples. The machine is valued by the scientific community involved in space relevant topics as an excellent experimental tool to conduct pre-studies, for example, before sending samples into space. We have developed a novel version of the traditional RPM to broaden its operative range. This novel version has now become interesting to researchers who are working in the field of tissue engineering, particularly those interested in alternative methods for three-dimensional (3D) cell culturing. The main modifications concern the cell culture condition and the algorithm that controls the movement of the frames for the nullification of gravity. An incubator was integrated into the inner frame of the RPM allowing precise control over the cell culture environment. Furthermore, several feed-throughs now allow a permanent supply of gas like CO₂. All these modifications substantially improve conditions to culture cells; furthermore, the rewritten software responsible for controlling the movement of the frames enhances the quality of the generated microgravity. Cell culture experiments were carried out with human lymphocytes on the novel RPM model to compare the obtained response to the results gathered on an older well-established RPM as well as to data from space flights. The overall outcome of the tests validates this novel RPM for cell cultivation under simulated microgravity conditions.

BibTeX:

@ARTICLE{Wues:etal:14,
  AUTHOR = 	 {Wuest, S. L. and Richard, S. and Walther, I. and Furrer, R. and Anderegg, R. and Sekler, J. and Egli, M.},
  TITLE = 	 {A Novel Microgravity Simulator Applicable for Three-Dimensional Cell Culturing},
  JOURNAL = 	 {Microgravity Sci. Technol.},
  FJOURNAL = 	 {Microgravity Science and Technology},
  YEAR = 	 {2014},
  DOI =          {10.1007/s12217-014-9364-2},
  VOLUME = 	 {26},
  NUMBER = 	 {2},
  PAGES = 	 {77--88},
  DISPLAY =      {Wuest, S. L., Richard, S., Walther, I., Furrer, R., Anderegg, R., Sekler, J. and Egli, M. (2014). A Novel Microgravity Simulator Applicable for Three-Dimensional Cell Culturing. Microgravity Science and Technology, 26(2), 77–88.},
}

Furrer, R., Kirchner, N. and Jakobsson, M. (2014). A Cross-polar Modeling Approach to Hindcast Paleo-Arctic Mega Icebergs: a Storyboard. In: Pardo-Igúzquiza, E., et al. (Eds.) Mathematics of Planet Earth, Springer, 41-44. [Abstract] [BibTeX]

Abstract: Recent geophysical mapping of the Arctic seafloor has revealed extensive erosion caused by ice and glacial landforms on ridge crests and plateaus where present water depths are shallower than $\approx$1000\,m. Such erosion stems from thick outlet glaciers and massive ice shelf complexes. Cores and glacigenic landforms suggest that the largest ice shelf complex was confined to the Amerasian sector of the Arctic Ocean, roughly 135'000 years ago. We apply a peak over threshold approach to assess whether the calving fronts of this ice shelf complex comprise a likely source of the deep draft icebergs responsible for the mapped plow marks. This approach is novel to modeling Arctic paleoglacial configurations. Predicted extreme calving front drafts match observed deep-draft iceberg marks if the ice shelf complex is sufficiently large.
We explain the methodology of Kirchner, Furrer, Jakobsson and coauthors \cite{kirc:furr:etal:13} in a storyboard framework, i.e., with figures and sketches. Here, we extend their approach by using shelf specific threshold selection, an alternative estimate to scale `coastlines', supervised pooling of estimates and uncertainty estimates based on parametric bootstrap. For theoretical details as well as details about the precise origin and preprocessing of the data we refer to \cite{kirc:furr:etal:13}, much of the statistical theory is covered in \cite{coles,Embr:etal}.

BibTeX:

@InProceedings{Furr:Kirc:Jako:14,
    AUTHOR = {Furrer,  R. and Kirchner, N. and Jakobsson,  M.},
      YEAR = {2014},
     TITLE = {A Cross-polar Modeling Approach to Hindcast Paleo-{Arctic} Mega Icebergs: a Storyboard},
 BOOKTITLE = {Mathematics of Planet Earth},
     PAGES = {41-44},
       DOI = {10.1007/978-3-642-32408-6_10},
    EDITOR = {Pardo-Igúzquiza, E. and Guardiola-Albert, C. and Heredia, J.
             and Moreno-Merino, L. and Durán, J.J. and Vargas-Guzmán, J.A.},
    SERIES = {Lecture Notes in Earth System Sciences},
 PUBLISHER = {Springer},
      NOTE = {Proceedings of the 15th Annual Conference of the International 
              Association for Mathematical Geosciences},
      ISBN = {978-3-642-32407-9},
   FUNDING = {SNSF 129782, 143282; URPP SB/FG, GCB},
   DISPLAY = {Furrer, R., Kirchner, N. and Jakobsson, M. (2014). A Cross-polar Modeling Approach to Hindcast Paleo-Arctic Mega Icebergs: a Storyboard. In: Pardo-Igúzquiza, E., et al. (Eds.) Mathematics of Planet Earth, Springer, 41–44.},
}

2013

Gerber, F.,⁺ Marty, F.,⁺ Eijkel, G. B.,⁺ Basler, K., Brunner, E., Furrer, R.^| and Heeren, R. M. A.^| (2013). Multi order correction algorithms to remove image distortions from mass spectrometry imaging datasets. Analytical Chemistry 85(21), 10249–10254. [Abstract] [BibTeX]

Abstract: Time-of-flight secondary ion mass spectrometry imaging is a rapidly evolving technology. Its main application is the study of the distribution of small molecules on biological tissues. The sequential image acquisition process remains susceptible to measurement distortions that can render imaging data less analytically useful. Most of these artifacts show a repetitive nature from tile to tile. Here we statistically describe these distortions and derive two different algorithms to correct them. Both a generalized linear model approach and the linear discriminant analysis approach are able to increase image quality for negative and positive ion mode data sets. Additionally, performing simulation studies with repetitive and nonrepetitive tiling error we show that both algorithms are only removing repetitive distortions. It is further shown that the spectral component of the data set is not altered by the use of these correction methods. Both algorithms presented in this work greatly increase the image quality and improve the analytical usefulness of distorted images dramatically.

BibTeX:

@ARTICLE{Gerb:etal:13,
    AUTHOR = {Florian Gerber and Florian Marty and Gert B. Eijkel and Konrad Basler and Erich Brunner and Reinhard Furrer and Ron M. A. Heeren},
      YEAR = {2013},
     TITLE = {Multi order correction algorithms to remove image distortions from mass spectrometry imaging datasets},
   JOURNAL = {Anal. Chem.},
  FJOURNAL = {Analytical Chemistry},
    VOLUME = {85},
    NUMBER = {21},
     PAGES = {10249-10254},
       DOI = {10.1021/ac402018e},
      PMID = {24093946},
   FUNDING = {URPP SB/FG; other},
   DISPLAY = {Gerber, F., Marty, F.,+ Eijkel, G. B., Basler, K., Brunner, E., Furrer, R. and Heeren, R. M. A. (2013). Multi order correction algorithms to remove image distortions from mass spectrometry imaging datasets. Analytical Chemistry 85(21), 10249–10254.}, 
}

Heersink, D. K. and Furrer, R. (2013). Sequential spatial analysis of large datasets with applications to modern earthwork compaction roller measurement values. Spatial Statistics, 6, 41–56. [Abstract] [BibTeX]

Abstract: In the context of road construction, modern earthwork compaction rollers equipped with sensors collect a virtually continuous flow of soil property measurements. This sequential, spatial data can be utilized to improve the quality control of the compaction process through the introduction of intelligent compaction. These roller measurement values are observed indirectly through non-linear measurement operators, non-stationary, inherently multivariate with complex correlation structures, and collected in huge quantities. The problem of modeling and estimation in a spatially correlated setting with large amounts of data is well known and many approaches can be found in the literature. Very few studies have been completed investigating sequential, spatially correlated data outside of a point process framework. We propose a sequential, spatial mixed-effects model and develop a sequential, spatial backfitting algorithm to estimate fixed effects and several independent, spatially correlated processes. This new algorithm is demonstrated in a simulation study and applied to earthwork compaction data.

Keywords: Backfitting; Hierarchical multivariate spatial models; Quasi-Kronecker; Sparse matrix; Spatial mixed-effects

BibTeX:

@ARTICLE{Heer:Furr:13,
    AUTHOR = {Heersink, D. K. and Furrer,  R.},
      YEAR = {2013},
     TITLE = {Sequential spatial analysis of large datasets with
              applications to modern earthwork compaction
              roller measurement values},
   JOURNAL = {Spatial Statistics},
  FJOURNAL = {Spatial Statistics},
     VOLUME = {6},
     PAGES = {41-56},
       DOI = {10.1016/j.spasta.2013.07.002},
   FUNDING = {SNF 200021-129782; US NCHRP 21-09},
   DISPLAY = {Heersink, D. K. and Furrer, R. (2013). Sequential spatial analysis of large datasets with applications to modern earthwork compaction roller measurement values. Spatial Statistics, 6, 41–56.}, 
}

Kirchner, N.,⁺ Furrer, R.,⁺ Jakobsson, M., Zwally, H. J. and Robbins, J. W. (2013). Statistical modeling of a former Arctic Ocean ice shelf complex using Antarctic analogies. Journal of Geophysical Research: Earth Surface, 118(2), 1105–1117. [Abstract] [BibTeX]

Abstract: Geophysical mapping and coring of the central Arctic Ocean seafloor provide evidence for repeated occurrences of ice sheet/ice shelf complexes during previous glacial periods. Several ridges and bathymetric highs shallower than present water depths of ∼1000 m show signs of erosion from deep-drafting (armadas of) icebergs, which originated from thick outlet glaciers and ice shelves. Mapped glacigenic landforms and dates of cored sediments suggest that the largest ice shelf complex was confined to the Amerasian sector of the Arctic Ocean during Marine Isotope Stage (MIS) 6. However, the spatial extent of ice shelves can not be well reconstructed from occasional groundings on bathymetric highs. Therefore, we apply a statistical approach to provide independent support for an extensive MIS 6 ice shelf complex, which previously was inferred only from interpretation of geophysical and geological data. Specifically, we assess whether this ice shelf complex comprises a likely source of the deep-draft icebergs responsible for the mapped scour marks. The statistical modeling is based on exploiting relations between contemporary Antarctic ice shelves and their local physical environments and the assumption that Arctic Ocean MIS 6 ice shelves scale similarly. Analyzing ice thickness data along the calving front of contemporary ice shelves, a peak over threshold method is applied to determine sources of deep-drafting icebergs in the Arctic Ocean MIS 6 ice shelf complex. This approach is novel to modeling Arctic paleoglacial configurations. Predicted extreme calving front drafts match observed deep-draft iceberg scours if the ice shelf complex is sufficiently large.

Keywords: Arctic Ocean ice shelves; extreme value theory; deep-draft ice berg scours; multivariate linear model; ICESat data in Arctic-Antarctic analogy approach

BibTeX:

@ARTICLE{Kirc:Furr:etal:13,
    AUTHOR = {Kirchner, N. and Furrer, R. and Jakobsson, M. and Zwally, H. J. and Robbins, J. W.},
      YEAR = {2013},
     TITLE = {Statistical modeling of a former {Arctic Ocean} ice shelf complex using {Antarctic} analogies},
   JOURNAL = {J. Geophys. Res. Earth Surf.},
  FJOURNAL = {Journal of Geophysical Research: Earth Surface},
    VOLUME = {118},
    NUMBER = {2},
     PAGES = {1105-1117},
       DOI = {10.1002/jgrf.20077},
   FUNDING = {SNSF 129782, 143282; URPP SB/FG},
   DISPLAY = {Kirchner, N., Furrer, R., Jakobsson, M., Zwally, H. J. and Robbins, J. W. (2013). Statistical modeling of a former Arctic Ocean ice shelf complex using Antarctic analogies. Journal of Geophysical Research: Earth Surface, 118(2), 1105–1117.},
}

de Jong, R., Schaepman, M. E., Furrer, R. de Bruin, S. and Verburg, P. H. (2013). Spatial relationship between climatologies and changes in global vegetation activity. Global Change Biology, 19(6), 1953–1964. [Abstract] [BibTeX]

Abstract: Vegetation forms a main component of the terrestrial biosphere and plays a crucial role in land-cover and climate-related studies. Activity of vegetation systems is commonly quantified using remotely sensed vegetation indices (VI). Extensive reports on temporal trends over the past decades in time series of such indices can be found in literature. However, little remains known about the processes underlying these changes at large spatial scales. In this study, we aimed at quantifying the spatial relationship between changes in potential climatic growth constraints (i.e. temperature, precipitation and incident solar radiation) and changes in vegetation activity (1982–2008). We demonstrate an additive spatial model with 0.5° resolution, consisting of a regression component representing climate-associated effects and a spatially correlated field representing the combined influence of other factors, including land-use change. Little over 50% of the spatial variance could be attributed to changes in climatologies; conspicuously, many greening trends and browning hotspots in Argentina and Australia. The nonassociated model component may contain large-scale human interventions, feedback mechanisms or natural effects, which were not captured by the climatologies. Browning hotspots in this component were especially found in subequatorial Africa. On the scale of land-cover types, strongest relationships between climatologies and vegetation activity were found in forests, including indications for browning under warming conditions (analogous to the divergence issue discussed in dendroclimatology).

Keywords: climate- and human-induced change; climatologies; Gaussian random field; growth constraints; regression; spatial additive model; vegetation-activity trends

BibTeX:

@ARTICLE{deJo:etal:13,
    AUTHOR = {de Jong, Rogier and Schaepman, Michael E. and Furrer, Reinhard and de Bruin, Sytze and Verburg, Peter H.},
      YEAR = {2013},
     TITLE = {Spatial relationship between climatologies and changes in global vegetation activity},
   JOURNAL = {Glob. Change Biol.},
  FJOURNAL = {Global Change Biology},
    VOLUME = {19},
    NUMBER = {6},
     PAGES = {1953–1964},
       DOI = {10.1111/gcb.12193},
      PMID = {23512439}, 
   FUNDING = {URPP GCB},
   DISPLAY = {de Jong, R., Schaepman, M. E., Furrer, R. de Bruin, S. and Verburg, P. H. (2013). Spatial relationship between climatologies and changes in global vegetation activity. Global Change Biology, 19(6), 1953–1964.}, 
}

2012

Benigni, M. and Furrer, R. (2012). Spatio-temporal improvised explosive device monitoring: improving detection to minimise attacks. Journal of Applied Statistics, 39(11) 2493–2508. [Abstract] [BibTeX]

Abstract:

The improvised explosive device (IED) is a weapon of strategic influence on today's battlefield. IED detonations occur predominantly on roads, footpaths, or trails. Therefore, locations are best described when constrained to the road network, and some spaces on the network are more dangerous at specific times of the day. We propose a statistical model that reduces the spatial location to one dimension and uses a cyclic time as a second dimension. Based on the Poisson process methodology, we develop normalised, inhomogeneous, bivariate intensity functions measuring the threat of attack to support resourcing decisions. A simulation and an analysis of attacks on a main supply route in Baghdad are given to illustrate the proposed methods. Additionally, we provide an overview of the growing demand for the analysis efforts in support of operations in Afghanistan and Iraq, and provide an extensive literature review of developments in counter-IED analysis.

Keywords: Periodic spatio-temporal cluster, linear referencing, Poisson process, risk, intensity function.

BibTeX:

@ARTICLE{Beni:Furr:12,
    AUTHOR = {Benigni, Matthew and Furrer, Reinhard},
     TITLE = {Spatio-temporal improvised explosive device monitoring: improving detection to minimise attacks},
      YEAR = {2012},
   JOURNAL = {J. Appl. Stat.},
  FJOURNAL = {Journal of Applied Statistics},
    VOLUME = {39},
    NUMBER = {11},
     PAGES = {2493--2508},
       DOI = {10.1080/02664763.2012.719222},
   DISPLAY = {Benigni, M. and Furrer, R. (2012). Spatio-temporal improvised explosive device monitoring: improving detection to minimise attacks. Journal of Applied Statistics, 39(11) 2493–2508.}, 
}

Furrer, R., Genton, M. G. and Nychka, D. (2012). Erratum and Addendum to: “Covariance Tapering for Interpolation of Large Spatial Datasets” published in the Journal of Computational and Graphical Statistics, 15, 502–523. Journal of Computational and Graphical Statistics 21(3), 823-824. [Summary] [BibTeX] [Auxiliary material]

Summary:

The Taper Condition stated in Furrer et al. (2006) (FGN hereafter) should either exclude the case ε = 0 or be slightly rephrased. The proof of Proposition 1 in FGN shows that the limit superior of (A.1) is bounded but it does not explicitly show that it is equal to the limit inferior for ε = 0. It is, moreover, possible to construct tapers satisfying the taper condition which lead to non-existing limits (A.1), an example is the sum of a spherical and triangular covariance function in IR. To include the case ε = 0 a slightly stronger tail condition on the spectral density of the taper is required. The supplementary material gives a proof of Proposition 1 of FGN under this modified taper condition combining the cases k > ν + d/2 (ε > 0) and k = ν + d/2 (ε = 0).

BibTeX:

 @ARTICLE{Furr:Gent:Nych:12,
    AUTHOR = {R. Furrer and M. G. Genton and D. Nychka},
     TITLE = {Erratum and Addendum to: “Covariance Tapering for Interpolation of Large Spatial Datasets” published in the Journal of Computational and Graphical Statistics, 15, 502–523},
      YEAR = {2012},	
   JOURNAL = {J. Comput. Graph. Stat.},
  FJOURNAL = {Journal of Computational and Graphical Statistics},
    VOLUME = {21},
    NUMBER = {3},
     PAGES = {823-824},
       DOI = {10.1080/10618600.2012.712502},
   DISPLAY = {Furrer, R., Genton, M. G. and Nychka, D. (2012). Erratum and Addendum to: “Covariance Tapering for Interpolation of Large Spatial Datasets” published in the Journal of Computational and Graphical Statistics, 15, 502–523. Journal of Computational and Graphical Statistics 21(3), 823-824.}, 
}

Furrer, R., Geinitz, S. and Sain, S. R. (2012). Assessing variance components of general circulation model output field. Environmetrics, 23(5), 440–450. [Abstract] [BibTeX]

Abstract:

Recent internationally coordinated efforts have used deterministic climate models for a common set of experiments and have produced large datasets of future climate projections. These ensembles are subject to many sources of variability, and we propose an analysis of variance procedure to quantify the contribution from several sources to the overall variation. This procedure is based on a Bayesian linear model parameterization and is applicable for large spatial data. A key feature is that individual sources of variability are modeled through batches and assessed through the batches' superpopulation variance, individual batch level predictions, and finite population covariance. Further, for a large class of models, we show that the full posterior can be factored into conditionally independent distributions, consisting of a batch's superpopulation and batch levels. By doing so, the need for MCMC methods is obviated. Finally, this approach is applied to decadal summer temperatures for different climate models and various scenarios.

Keywords: Multivariate ANOVA; Spatial data; Mixed model; Bayesian inference.

BibTeX:

@ARTICLE{Furr:Gein:Sain:12,
    AUTHOR = {Reinhard Furrer and Steven Geinitz and Stephan R. Sain},
     TITLE = {Assessing variance components of general circulation model output field},
      YEAR = {2012},
   JOURNAL = {Environmetrics},
  FJOURNAL = {Environmetrics},
    VOLUME = {23},
    NUMBER = {5},
     PAGES = {440--450},
       DOI = {10.1002/env.2139},
   DISPLAY = {Furrer, R., Geinitz, S. and Sain, S. R. (2012). Assessing variance components of general circulation model output field. Environmetrics, 23(5), 440–450.}, 
}

Heersink, D. K. and Furrer, R. (2012). On Moore-Penrose Inverses of Quasi-Kronecker Structured Matrices. Linear Algebra and its Applications, 436(3), 561–570. [Abstract] [BibTeX]

Abstract: The Moore--Penrose inverse and generalized inverse of $\A+\X_1\X_2^*$, where $\A$, $\X_1$, $\X_2$ are complex matrices are given under various assumptions. We use the result to derive the Moore--Penrose inverse and inverse for $\bdiag(\A_k)+ \bfu\v^*\otimes\bfE$ with $p$ complex matrices $\A_k$, two complex $p$-vectors $\bfu$ and $\v$ and a complex matrix $\bfE$. Such block structured matrices occur in hierarchical modeling of multivariate spatial or space-time Gaussian processes. For the latter we also give expressions of the determinant and of conditional variances.

Keywords: block-partitioned matrix, likelihood, hierarchical multivariate spatial models.

MSC: 15A09, 15A15, 62M30

BibTeX:

@ARTICLE{Heer:Furr:12,
    AUTHOR = {Heersink, D. K. and Furrer, R.},
      YEAR = {2012},
     TITLE = {On {Moore--Penrose} Inverses of Quasi-{Kronecker} Structured Matrices},
   JOURNAL = {Linear Algebra Appl.},
  FJOURNAL = {Linear Algebra and its Applications},
    VOLUME = {436},
    NUMBER = {3},
     PAGES = {561-570},
       DOI = {10.1016/j.laa.2011.07.009},
   FUNDING = {SNSF 200021-129782},
   DISPLAY = {Heersink, D. K. and Furrer, R. (2012). On Moore-Penrose Inverses of Quasi-Kronecker Structured Matrices. Linear Algebra and its Applications, 436(3), 561–570.}, 
}

2011

Furrer, R. and Genton, M. G. (2011). Aggregation-cokriging for Highly-Multivariate Spatial Data. Biometrika, 98(3), 615–631. [Abstract] [BibTeX]

Abstract: Best linear unbiased prediction of spatially correlated multivariate random processes, often called cokriging in geostatistics, requires the solution of a large linear system based on the covariance and cross-covariance matrix of the observations. For many problems of practical interest it is impossible to solve the linear system with direct methods. We propose an efficient linear unbiased predictor based on a linear aggregation of the covariables. The primary variable together with this single meta-covariable is used to perform cokriging. We discuss the optimality of the approach under different covariance structures, and use it to create re-analysis type high-resolution historical temperature fields.

Keywords: Climate; Cokriging; Eigendecomposition; Intrinsic process; Linear unbiased prediction.

BibTeX:

@ARTICLE{Furr:Gent:11,
    AUTHOR = {Furrer, R. and Genton, M. G.},
      YEAR = {2011},
     TITLE = {Aggregation-cokriging for Highly-Multivariate Spatial Data},
   JOURNAL = {Biometrika},
  FJOURNAL = {Biometrika},
    VOLUME = {98},
    NUMBER = {3},
     PAGES = {615--631},
       DOI = {10.1093/biomet/asr029},
   DISPLAY = {Furrer, R. and Genton, M. G. (2011). Aggregation-cokriging for Highly-Multivariate Spatial Data. Biometrika, 98(3), 615–631.}, 
}

Holmström, L., Pasanen, L., Furrer, R. and Sain, S. R. (2011). Scale Space Multiresolution Analysis of Random Signals. Computational Statistics and Data Analysis, 55, 2840–2855. [Abstract] [BibTeX]

Abstract: A method to capture the scale-dependent features in a random signal is proposed with the main focus on images and spatial fields defined on a regular grid. A technique based on scale space smoothing is used. However, where the usual scale space analysis approach is to suppress detail by increasing smoothing progressively, the proposed method instead considers differences of smooths at neighboring scales. A random signal can then be represented as a sum of such differences, a kind of a multiresolution analysis, each difference representing details relevant at a particular scale or resolution. Bayesian analysis is used to infer which details are credible and which are just artifacts of random variation. The applicability of the method is demonstrated using noisy digital images as well as global temperature change fields produced by numerical climate prediction models.

Keywords: Scale space smoothing, Bayesian methods, Image analysis, Climate research

BibTeX:

@ARTICLE{Holm:etal:11,
    AUTHOR = {Holmstr\"om, L. and Pasanen, L. and Furrer, R. and Sain, S. R.},
      YEAR = {2011},
     TITLE = {Scale Space Multiresolution Analysis of Random Signals},
   JOURNAL = {Comput. Stat. Data An.},
  FJOURNAL = {Computational Statistics \& Data Analysis},
    VOLUME = {55},
    NUMBER = {},
     PAGES = {2840--2855},
       DOI = {10.1016/j.csda.2011.04.011},
   DISPLAY = {Holmström, L., Pasanen, L., Furrer, R. and Sain, S. R. (2011). Scale Space Multiresolution Analysis of Random Signals. Computational Statistics and Data Analysis, 55, 2840–2855.}, 
}

Sain, S. R., Furrer, R., Cressie, N. (2011). A Spatial Analysis of Multivariate Output from Regional Climate Models. Annals of Applied Statistics, 5(1), 150–175. [Abstract] [BibTeX]

Abstract: Climate models have become an important tool in the study of climate and climate change, and ensemble experiments consisting of multiple climate-model runs are used in studying and quantifying the uncertainty in climate-model output. However, there are often only a limited number of model runs available for a particular experiment, and one of the statistical challenges is to characterize the distribution of the model output. To that end, we have developed a multivariate hierarchical approach, at the heart of which is a new representation of a multivariate Markov random field. This approach allows for flexible modeling of the multivariate spatial dependencies, including the cross-dependencies between variables. We demonstrate this statistical model on an ensemble arising from a regional-climate-model experiment over the western United States, and we focus on the projected change in seasonal temperature and precipitation over the next 50 years.

Keywords: Lattice Data, Markov Random Field (MRF), Conditional Autoregressive (CAR) Model, Bayesian Hierarchical Model, Climate Change.

BibTeX:

@ARTICLE{Sain:Furr:Cres:11,
    AUTHOR = {Sain, S. R. and Furrer, R. and Cressie, N.},
      YEAR = {2011},
     TITLE = {A Spatial Analysis of Multivariate Output from Regional Climate Models},
   JOURNAL = {Ann. Appl. Stat.},
  FJOURNAL = {Annals of Applied Statistics},
    VOLUME = {5},
    NUMBER = {1},
     PAGES = {150-175},
       DOI = {10.1214/10-AOAS369},
   DISPLAY = {Sain, S. R., Furrer, R., Cressie, N. (2011). A Spatial Analysis of Multivariate Output from Regional Climate Models. Annals of Applied Statistics, 5(1), 150–175.}, 
}

2010

Furrer, E. M., Katz, R. W., Walter, M. D. and Furrer, R. (2010). Statistical modeling of hot spells and heat waves. Climate Research, 43(3), 191-205. [Abstract] [BibTeX]

Abstract: Although hot spells and heat waves are considered extreme meteorological phenomena, the statistical theory of extreme values has only rarely, if ever, been applied. To address this shortcoming, we extended the point process approach to extreme value analysis to model the frequency, duration, and intensity of hot spells. The annual frequency of hot spells was modeled by a Poisson distribution, and their length by a geometric distribution. To account for the temporal dependence of daily maximum temperatures within a hot spell, the excesses over a high threshold were modeled by a conditional generalized Pareto distribution, whose scale parameter depends on the excess on the previous day. Requiring only univariate extreme value theory, our proposed approach is simple enough to be readily generalized to incorporate trends in hot spell characteristics. Through a heat wave simulator, the statistical modeling of hot spells can be extended to apply to more full-fledged heat waves, which are difficult to model directly. Our statistical model for hot spells was fitted to time series of daily maximum temperature during the summer heat wave season in Phoenix, Arizona (USA), Fort Collins, Colorado (USA), and Paris, France. Trends in the frequency, duration, and intensity of hot spells were fitted as well. The heat wave simulator was used to convert any such trends into the corresponding changes in the characteristics of heat waves. By being based at least in part on extreme value theory, our proposed approach is both more realistic and more flexible than techniques heretofore applied to model hot spells and heat waves.

Keywords: Climate change; Clustering of extremes; Generalized Pareto distribution; Point process approach; Heat wave simulator.

BibTeX:

@ARTICLE{Furr:etal:10,
    AUTHOR = {Furrer, E. M. and Katz, R. W. and  Walter, M. D. and Furrer, R},
      YEAR = {2010},
     TITLE = {Statistical modeling of hot spells and heat waves},
   JOURNAL = {Clim. Res.},
  FJOURNAL = {Climate Research},
    VOLUME = {43},
    NUMBER = {3},
     PAGES = {191--205},
       DOI = {10.3354/cr00924},
}

Krembs, F. J., Siegrist, R. L., Crimi, M. L., Furrer, R. and Petri, B. G. (2010). ISCO for Groundwater Remediation: Analysis of Field Applications and Performance. Ground Water Monitoring & Remediation, 30(4): 42–53. [Abstract] [BibTeX]

Abstract: A critical analysis of in situ chemical oxidation (ISCO) projects was performed to characterize situations in which ISCO is being implemented, how design and operating parameters are typically employed, and to determine the performance results being achieved. This research involved design of a database, acquisition and review of ISCO project information, population of the database, and analyses of the database using statistical methods. Based on 242 ISCO projects included in the database, ISCO has been used to treat a variety of contaminants; however, chlorinated solvents are by far the most common. ISCO has been implemented at sites with varied subsurface conditions with vertical injection wells and direct push probes being the most common delivery methods. ISCO has met and maintained concentrations below maximum contaminant levels (MCLs), although not at any sites where dense nonaqueous phase liquids (DNAPL) were presumed to be present. Alternative cleanup levels and mass reduction goals have also been attempted, and these less stringent goals are met with greater frequency than MCLs. The use of pilot testing is beneficial in heterogeneous geologic media, but not so in homogeneous media. ISCO projects cost $220,000 on average, and cost on average $94/yd³ of target treatment zone. ISCO costs vary widely based on the size of the treatment zone, the presence of DNAPL, and the oxidant delivery method. No case studies were encountered in which ISCO resulted in permanent reductions to microbial populations or sustained increases in metal concentrations in groundwater at the ISCO-treated site.

BibTeX:

@ARTICLE{Krem:etal:10,
    AUTHOR = {Krembs, F. J., Siegrist, R. L., Crimi, M. L., Furrer, R. and Petri, B. G.},
      YEAR = {2010},
     TITLE = {ISCO for Groundwater Remediation: Analysis of Field Applications and Performance},
   JOURNAL = {Ground Water Monitoring \& Remediation},
  FJOURNAL = {Ground Water Monit. Remediat.},
    VOLUME = {30},
    NUMBER = {4},
     PAGES = {42--53},
       DOI = {10.1111/j.1745-6592.2010.01312.x},
}

Facas, N., Mooney, M. A. and Furrer, R. (2010). Anisotropy in the Spatial Distribution of Roller-Measured Soil Stiffness. International Journal of Geomechanics, 10(4), 129-135. [Abstract] [BibTeX]

Abstract: Geostatistical analysis of roller-measured soil properties (from continuous compaction control and intelligent compaction) is required for advanced quality control/quality assurance of earthwork and asphalt compaction. This paper explores the existence of anisotropy in the spatial distribution of roller-measured soil stiffness and the effect of anisotropy on kriging. Field testing was conducted to collect roller measurement value (MV) data over typical roadway embankment evaluation areas and on a large square area to enable a robust investigation of anisotropy. Semi-variogram analysis of the field data clearly indicates that range anisotropy exists. The spatial distribution of roller MV data is different in the longitudinal x direction than in the transverse y direction. Magnitudes of range anisotropy (x range/y range) varied from 2.4 to over 5. The observed range anisotropy is not due to the roller measurement system; rather, it is likely due to the directional nature of earthwork construction activities and to alignment geometry. The influence of anisotropy on kriging was found to be significant when considering the use of kriged data in earthwork specifications. The error introduced by not accounting for anisotropy in kriging varied from 5% to 17% when considering pass to pass or layer to layer map analysis. Anisotropy in the spatial distribution of roller MV data should be factored into kriging and other geostatistical analyses. For typical earthwork area geometries, the roller mapping procedure requires slight modification to determine the y range and anisotropy ratio.

BibTeX:

@ARTICLE{Faca:Moon:Furr:10,
    AUTHOR = {Facas, N. and Mooney, M. A. and Furrer, R.},
      YEAR = {2010},
     TITLE = {Anisotropy in the Spatial Distribution of Roller-Measured Soil Stiffness},
   JOURNAL = {Int. J. Geomech.},
  FJOURNAL = {International Journal of Geomechanics},
    VOLUME = {10},
    NUMBER = {4},
     PAGES = {129-135},
       DOI = {10.1061/(ASCE)GM.1943-5622.0000053},
}

Furrer, R. and Sain, S. R. (2010). spam: A Sparse Matrix R Package with Emphasis on MCMC Methods for Gaussian Markov Random Fields. Journal of Statistical Software, 36(10), 1--25. [Abstract] [BibTeX]

Abstract: spam is an R package for sparse matrix algebra with emphasis on a Cholesky factorization of sparse positive definite matrices. The implemantation of spam is based on the competing philosophical maxims to be competitively fast compared to existing tools and to be easy to use, modify and extend. The first is addressed by using fast Fortran routines and the second by assuring S4 and S3 compatibility. One of the features of spam is to exploit the algorithmic steps of the Cholesky factorization and hence to perform only a fraction of the workload when factorizing matrices with the same sparseness structure. Simulations show that exploiting this break-down of the factorization results in a speed-up of about a factor 5 and memory savings of about a factor 10 for large matrices and slightly smaller factors for huge matrices. The article is motivated with Markov chain Monte Carlo methods for Gaussian Markov random fields, but many other statistical applications are mentioned that profit from an efficient Cholesky factorization as well.

Keywords: Cholesky factorization, Compactly supported covariance function, Compressed sparse row format, Symmetric positive-definite matrix, Stochastic modeling, S3/S4.

BibTeX:

@ARTICLE{Furr:Sain:10,
    AUTHOR = {Furrer, R. and Sain, S. R.},
      YEAR = {2010},
     TITLE = {{spam}: {A} Sparse Matrix {R} Package with Emphasis on {MCMC} Methods for {G}aussian {M}arkov Random Fields},
   JOURNAL = {J. Stat. Softw.},
  FJOURNAL = {Journal of Statistical Software},
    VOLUME = {36},
    NUMBER = {10},
     PAGES = {1--25},
       URL = {http://www.jstatsoft.org/v36/i10/},
}

Sain, S. R. and Furrer, R. (2010). Combining Climate Model Output via Model Correlations, Stochastic Environmental Research and Risk Assessment, 24(6), 821--829. [Abstract] [BibTeX]

Abstract: In climate science, collections of climate model output, usually referred to as ensembles, are commonly used devices to study uncertainty in climate model experiments. The ensemble members may reflect variation in initial conditions, different physics implementations, or even entirely different climate models. However, there is a need to deliver a unified product based on the ensemble members that reflects the information contained in whole of the ensemble. We propose a technique for creating linear combinations of ensemble members where the weights are constructed from estimates of variation and correlation both within and between ensemble members. At the heart of this approach is a Bayesian hierarchical model that allows for estimation of the correlation between ensemble members as well as the study of the impact of uncertainty in the parameter estimates of the hierarchical model on the weights. The approach is demonstrated on an ensemble of regional climate model (RCM) output.

Keywords: Model averaging, Model correlations, Total variation, Regional climate models, Bayesian hierarchical model

BibTeX:

@ARTICLE{Sain:Furr:10,
    AUTHOR = {Sain, S. R. and Furrer, R.},
      YEAR = {2010},
     TITLE = {Combining climate model output via model correlations},
   JOURNAL = {Stoch. Environ. Res. Risk Assess.},
  FJOURNAL = {Stochastic Environmental Research and Risk Assessment},
    VOLUME = {24},
    NUMBER = {6},
     PAGES = {821--829},
       DOI = {10.1007/s00477-010-0380-5},
}

Knutti, R. and Furrer, R. and Tebaldi, C. and Cermak, J. and Meehl, G. A. (2010). Challenges in combining projections from multiple climate models. Journal of Climate, 23(10), 2739-2758. [Abstract] [BibTeX]

Abstract: Recent coordinated efforts, in which numerous general circulation climate models have been run for a common set of experiments, have produced large datasets of projections of future climate for various scenarios. Those multimodel ensembles sample initial conditions, parameters, and structural uncertainties in the model design, and they have prompted a variety of approaches to quantifying uncertainty in future climate change. International climate change assessments also rely heavily on these models. These assessments often provide equal-weighted averages as best-guess results, assuming that individual model biases will at least partly cancel and that a model average prediction is more likely to be correct than a prediction from a single model based on the result that a multimodel average of present-day climate generally outperforms any individual model. This study outlines the motivation for using multimodel ensembles and discusses various challenges in interpreting them. Among these challenges are that the number of models in these ensembles is usually small, their distribution in the model or parameter space is unclear, and that extreme behavior is often not sampled. Model skill in simulating present-day climate conditions is shown to relate only weakly to the magnitude of predicted change. It is thus unclear by how much the confidence in future projections should increase based on improvements in simulating present-day conditions, a reduction of intermodel spread, or a larger number of models. Averaging model output may further lead to a loss of signal—for example, for precipitation change where the predicted changes are spatially heterogeneous, such that the true expected change is very likely to be larger than suggested by a model average. Last, there is little agreement on metrics to separate “good” and “bad” models, and there is concern that model development, evaluation, and posterior weighting or ranking are all using the same datasets. While the multimodel average appears to still be useful in some situations, these results show that more quantitative methods to evaluate model performance are critical to maximize the value of climate change projections from global models.

Keywords: Climate models, Ensembles, Diagnostics, Climate prediction

BibTeX:

@ARTICLE{Knut:etal:10,
    AUTHOR = {Knutti, R. and Furrer, R. and  Tebaldi, C. and Cermak, J. and  Meehl, G. A.},
      YEAR = {2010},
     TITLE = {Challenges in combining projections from multiple climate models},
   JOURNAL = {J. Clim.},
  FJOURNAL = {Journal of Climate},
    VOLUME = {23},
    NUMBER = {10},
     PAGES = {2739-2758},
       DOI = {10.1175/2009JCLI3361.1},
}

2009

Furrer, R. and Sain, S. R. (2009). Spatial Model Fitting for Large Datasets with Applications to Climate and Microarray Problems. Statistics and Computing, 19(2), 113-128, doi:10.1007/s11222-008-9075-x. [Abstract] [BibTeX]

Abstract: Many problems in the environmental and biological sciences involve the analysis of large quantities of data. Further, the data in these problems are often subject to various types of structure and, in particular, spatial dependence. Traditional model fitting often fails due to the size of the datasets since it is difficult to not only specify but also to compute with the full covariance matrix describing the spatial dependence. We propose a very general type of mixed model that has a random spatial component. Recognizing that spatial covariance matrices often exhibit a large number of zero or near-zero entries, covariance tapering is used to force near-zero entries to zero. Then, taking advantage of the sparse nature of such tapered covariance matrices, backfitting is used to estimate the fixed and random model parameters. The novelty of the paper is the combination of the two techniques, tapering and backfitting, to model and analyze spatial datasets several orders of magnitude larger than those datasets typically analyzed with conventional approaches. Results will be demonstrated with two datasets. The first consists of regional climate model output that is based on an experiment with two regional and two driver models arranged in a two-by-two layout. The second is microarray data used to build a profile of differentially expressed genes relating to cerebral vascular malformations, an important cause of hemorrhagic stroke and seizures.

Keywords: Mixed effects; Backfitting; Covariance Tapering; Sparse matrices.

BibTeX:

@ARTICLE{Furr:Sain:09,
    AUTHOR = {Furrer, R. and Sain, S. R.},
      YEAR = {2009},
     TITLE = {Spatial Model Fitting for Large Datasets with Applications to Climate and Microarray Problems},
   JOURNAL = {Stat. Comput.},
  FJOURNAL = {Statistics and Computing},
    VOLUME = {19},
    NUMBER = {2},
     PAGES = {113-128},
       DOI = {10.1007/s11222-008-9075-x},
}

Facas. N., Mooney, M. A., and Furrer, R. (2009). Geostatistical Analysis of Roller-Integrated Continuous Compaction Control Data. Bearing Capacity of Roads, Railways and Airfields, Tutumluer and Al-Qadi (eds.), Taylor and Francis Group, London, 1, 755-762.

Abstract:

Keywords: Mixed effects; Backfitting; Covariance Tapering; Sparse matrices.

BibTeX:

@ARTICLE{Furr:Sain:09,
    AUTHOR = {Furrer, R. and Sain, S. R.},
      YEAR = {2009},
     TITLE = {Spatial Model Fitting for Large Datasets with Applications to Climate and Microarray Problems},
   JOURNAL = {Stat. Comput.},
  FJOURNAL = {Statistics and Computing},
    VOLUME = {19},
    NUMBER = {2},
     PAGES = {113-128},
       DOI = {10.1007/s11222-008-9075-x},
}

2008

Mendez, P. F., Furrer, R., Ford, R. and Ordóñez, F. (2008). Scaling Laws as a Tool of Materials Informatics. JOM, 60(03), 60-66, doi:10.1007/s11837-008-0036-9. [Abstract] [BibTeX]

Abstract: This paper discusses the utility of scaling laws to materials informatics and presents the algorithm Scaling LAW (SLAW), useful to obtain scaling laws from statistical data. These laws can be used to extrapolate known materials property data to untested materials by using other more readily available information. This technique is independent of a characteristic length or time scale, so it is useful for a broad diversity of problems. In some cases, SLAW can reproduce the mathematical expression that would have been obtained through an analytical treatment of the problem. This technique was originally designed for mining statistical data in materials processing and materials behavior at a system level, and it shows promise for the study of the relationship between structure and properties in materials.

BibTeX:

@ARTICLE{Mend:etal:08,
    AUTHOR = {Mendez, P. F. and Furrer, R. and Ford, R. and Ord\'o\~nez, F.},
      YEAR = {2008},
     TITLE = {Scaling Laws as a Tool of Materials Informatics},
   JOURNAL = {JOM},
  FJOURNAL = {JOM},
    VOLUME = {60},
    NUMBER = {3},
     PAGES = {60-66},
       DOI = {http://dx.doi.org/10.1007/s11837-008-0036-9},
}

Kupper, T., de Alencastro, L. F., Gatsigazi, R., Furrer, R., Grandjean D. and Tarradellas J. (2008). Concentrations and specific loads of brominated flame retardants in sewage sludge. Chemosphere, 71(6), 1173-1180, doi:10.1016/j.chemosphere.2007.10.019. [Abstract] [BibTeX]

Abstract: Many substances related to human activities end up in wastewater and accumulate in sewage sludge. The present study focuses on two classes of brominated flame retardants: polybrominated diphenyl ethers (BDE28, BDE47, BDE49, BDE66, BDE85, BDE99, BDE100, BDE119, BDE138, BDE153, BDE154, BDE183, BDE209) and hexabromocyclododecane (HBCD) detected in sewage sludge collected from a monitoring network in Switzerland. Mean concentrations (n = 16 wastewater treatment plants) were 310, 149, 95 and 17 mu g per kg dry matter for decaBDE, HBCD, penta- and octaBDE, respectively. These numbers correspond well with other studies from European countries. DecaBDE, HBCD, penta- and octaBDE showed average specific loads (load per connected inhabitant per year) in sludge of 6.1, 3.3, 2.0 and 0.3 mg cap^-1 yr^-1, respectively. This is in line with consumption and storage of the compounds in the environment and the anthroposphere. Discrepancies observed for octaBDE and HBCD can be explained by the release from materials where these compounds are incorporated in and/or their degradation during anaerobic sludge treatment. Loads from different types of monitoring sites showed that brominated flame retardants ending up in sewage sludge originate mainly from surface runoff, industrial and domestic wastewater.

Keywords: Sources; Wastewater treatment plant; Polybrominated diphenyl ethers; Hexabromocyclododecane; Flux

BibTeX:

@ARTICLE{Kupp:etal:08,
    AUTHOR = {Kupper, T. and  De Alencastro, L.F. and Gatsigazi, R. and Furrer, R. and Grandjean, D. and Tarradellas J.},
      YEAR = {2008},
     TITLE = {Concentrations and specific loads of brominated flame retardants in sewage sludge},
   JOURNAL = {Chemosphere},
  FJOURNAL = {Chemosphere},
    VOLUME = {71},
    NUMBER = {6},
     PAGES = {1173-1180},
       DOI = {10.1016/j.chemosphere.2007.10.019},
      PMID = {18035395},
}

2007

Contributing author to Chapter 10 Global Climate Projections of the Working Group I contribution to the Intergovernmental Panel on Climate Change Fourth Assessment Report: Climate Change 2007: The Physical Science Basis, Cambridge University Press; ISBN 0521705967/0521880092.

Furrer, R, Sain, S. R., Nychka, D. and Meehl, G. A. (2007). Multivariate Bayesian Analysis of Atmosphere-Ocean General Circulation Models. Environmental and Ecological Statistics, 14(3), 249-266, doi:10.1007/s10651-007-0018-z. [Abstract] [BibTeX]

Abstract: Numerical experiments based on atmosphere-ocean general circulation models (AOGCMs) are one of the primary tools in deriving projections for future climate change. Although each AOGCM has the same underlying partial differential equations, modelling large scale effects, they have different small scale parameterisations and different discretisations to solve the equations, resulting in different climate projections. This motivates climate projections synthesized from results of several AOGCMs' output. We combine present day observations, present day and future climate projections in a single highdimensional hierarchical Bayes model. The challenging aspect is the modeling of the spatial processes on the sphere, the number of parameters and the amount of data involved. We pursue a Bayesian hierarchical model that separates the spatial response into a large scale climate change signal and an isotropic process representing small scale variability among AOGCMs. Samples from the posterior distributions are obtained with computer-intensive MCMC simulations. The novelty of our approach is that we use gridded, high resolution data covering the entire sphere within a spatial hierarchical framework. The primary data source is provided by the Coupled Model Intercomparison Project (CMIP) and consists of 9 AOGCMs on a 2.8 by 2.8 degree grid under several different emission scenarios. In this article we consider mean seasonal surface temperature and precipitation as climate variables. Extensions for our model are also discussed.

Keywords: Climate change; Spatial process; Spherical covariance, Hierarchical model; Large datasets; MCMC.

BibTeX:

@ARTICLE{Furr:Sain:Nych:Meeh:07,
  AUTHOR = {Furrer, R. and  Sain, S. R. and Nychka, D. W. and Meehl, G. A.},
   TITLE = {Multivariate {B}ayesian Analysis of Atmosphere-Ocean General Circulation Models},
    YEAR = {2007},
 JOURNAL = {Environ. Ecol. Stat.},
FJOURNAL = {Environmental and Ecological Statistics},
  VOLUME = {14},
  NUMBER = {3},
   PAGES = {249-266},
     DOI = {10.1007/s10651-007-0018-z},
}

Furrer, R., Knutti, R., Sain, S. R., Nychka, D. W. and Meehl, G. A. (2007). Spatial patterns of probabilistic temperature change projections from a multivariate Bayesian analysis. Geophysical Research Letters, 34, L06711, doi:10.1029/2006GL027754. [Abstract] [BibTeX]

Abstract: We present probabilistic projections for spatial patterns of future temperature change using a multivariate Bayesian analysis. The methodology is applied to the output from 21 global coupled climate models used for the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. The statistical technique is based on the assumption that spatial patterns of climate change can be separated into a large scale signal related to the true forced climate change and a small scale signal due to model bias and variability. The different scales are represented via dimension reduction techniques in a hierarchical Bayesian model. Posterior probabilities are obtained with a Markov chain Monte Carlo simulation. We show that with 66% (90%) probability 79% (48%) of the land areas warm by more than 2^oC by the end of the century for the SRES A1B scenario.

BibTeX:

@ARTICLE{Furr:Knut:Sain:Nych:Meeh:07,
    AUTHOR = {Furrer, R. and Knutti, R. and Sain, S. R. and Nychka, D. W. and Meehl, G. A.},
     TITLE = {Spatial patterns of probabilistic temperature change projections from a multivariate {B}ayesian analysis},
      YEAR = {2007},
   JOURNAL = {Geophys. Res. Lett.},
  FJOURNAL = {Geophysical Research Letters},
    VOLUME = {34},
     PAGES = {L06711},
       DOI = {10.1029/2006GL027754},
}

Brändli, R. C., Bucheli, T. D., Kupper, T., Furrer, R., Stahel, W. A., Stadelmann, F. X. and Tarradellas, J. (2007). Organic pollutants in compost and digestate. Part 1. Polychlorinated biphenyls, polycyclic aromatic hydrocarbons and markers. Journal of Environmental Moniting, 9, 456-464, doi:10.1039/b617101j. [Abstract] [BibTeX]

Abstract: In Europe, 9.3x10⁶t_{dry weight (dw)} of compost and digestate are produced per year. Most of this is applied to agricultural land, which can lead to considerable inputs of organic pollutants, such as polychlorinated biphenyls (PCB) and polycyclic aromatic hydrocarbons (PAH) to soil. This paper presents an inventory of the pollutant situation in source-separated composts, digestates and presswater in Switzerland by a detailed analysis of over 70 samples. PCB concentrations (sum PCB 28, 52, 101, 118, 138, 153, 180) were significantly higher in urban (median: 30 mg kg_dw^-1, n = 52) than in rural samples (median: 14 mg kg_dw^-1, n = 16). Together with low concentrations in general, this points to aerial deposition on compost input material as the major contamination pathway. Enantiomeric fractions of atropisometric PCB were close to racemic. Median PAH concentration was 3010 mg kg_dw^-1 (sum 15PAH, n = 69), and one quarter of the samples exhibited concentrations above the relevant Swiss guide value for compost (4000 mg kg_dw^-1). The levels were influenced by the treatment process (digestate > compost), the season of input material collection (spring-summer > winter > autumn), the particle size (coarse-grained > fine-grained), and maturity (mature > less mature). The main source of PAH in compost was pyrogenic, probably influenced mainly by liquid fossil fuel combustion and some asphalt abrasion, as suggested by multiple linear regression. This study, together with a companion paper reporting on other organic contaminates including emerging compound classes, provides a starting point for a better risk-benefit estimation of the application of compost and digestate to agricultural soil in Switzerland.

BibTeX:

@ARTICLE{Brae:Buch:Kupp:Furr:Stah:Stad:Tarr:07,
    AUTHOR = {Br\"andli, R. C. and Bucheli, T. D. and Kupper, T. and Furrer, R. and Stahel, W. A. and Stadelmann, F. X. and Tarradellas, J.},
     TITLE = {Organic pollutants in compost and digestate.  {P}art 1. {P}olychlorinated biphenyls, polycyclic aromatic hydrocarbons and markers},
      YEAR = {2007},
   JOURNAL = {J. Environ. Monit.},
  FJOURNAL = {Journal of Environmental Moniting},
    VOLUME = {9},
     PAGES = {456-464},
       DOI = {10.1039/b617101j},
      PMID = {17492091},
}

Furrer, R. and Naveau, P. (2007). Probability Weighted Moments Properties for Small Samples. Statistics and Probability Letters, 77(2), 190-195, doi:10.1016/j.spl.2006.06.009. [Abstract] [BibTeX]

Abstract: Probability weighted moments (PWM) are classically used in hydrology. Here we study their properties for small samples. Links between PWMs and the hazard rate ordering are identified. We propose PWM tail equivalences and derive explicit variances for PWM unbiased estimators.

Keywords: Generalized Pareto distribution; U-statistics

BibTeX:

@ARTICLE {Furr:Nave:07,
    AUTHOR = {Furrer, R. and Naveau, P.},
     TITLE = {Probability Weighted Moments Properties for Small Samples},
   JOURNAL = {Statist. Probab. Lett.},
  FJOURNAL = {Statistics and Probability Letters},
    VOLUME = {77},
      YEAR = {2007},
    NUMBER = {2},
     PAGES = {190-195},
}

Furrer, R. and Bengtsson, T. (2007). Estimation of High-dimensional Prior and Posteriori Covariance Matrices in Kalman Filter Variants. Journal of Multivariate Analysis, 98(2), 227-255, doi:10.1016/j.jmva.2006.08.003. [Abstract] [BibTeX]

Abstract: This work studies the effects of sampling variability in Monte Carlo-based methods to estimate very highdimensional systems. Recent focus in the geosciences has been on representing the atmospheric state using a probability density function, and, for extremely high-dimensional systems, various sample-based Kalman filter techniques have been developed to address the problem of real-time assimilation of system information and observations. As the employed sample sizes are typically several orders of magnitude smaller than the system dimension, such sampling techniques inevitably induce considerable variability into the state estimate, primarily through prior and posterior sample covariance matrices. In this article, we quantify this variability with mean squared error measures for two Monte Carlo-based Kalman filter variants: the ensemble Kalman filter and the ensemble square-root Kalman filter. Expressions of the error measures are derived under weak assumptions and show that sample sizes need to grow proportionally to the square of the system dimension for bounded error growth. To reduce necessary ensemble size requirements and to address rank-deficient sample covariances, covariance-shrinking (tapering) based on the Schur product of the prior sample covariance and a positive definite function is demonstrated to be a simple, computationally feasible, and very effective technique. Rules for obtaining optimal taper functions for both stationary as well as non-stationary covariances are given, and optimal taper lengths are given in terms of the ensemble size and practical range of the forecast covariance. Results are also presented for optimal covariance inflation. The theory is verified and illustrated with extensive simulations.

Keywords: Ensemble Kalman filter; Square-root filter; Matrix expansions; Shrinking; Tapering; Covariance boosting

BibTeX:

@ARTICLE{Furr:Beng:05,
    AUTHOR = {Furrer, R. and Bengtsson, T.},
      YEAR = {2007},
     TITLE = {Estimation of High-dimensional Prior and Posteriori Covariance Matrices in Kalman Filter Variants},
   JOURNAL = {J. Multivariate Anal.},
  FJOURNAL = {Journal of Multivariate Analysis},
    VOLUME = {98},
    NUMBER = {2},
     PAGES = {227-255},
       DOI = {10.1016/j.jmva.2006.08.003},
}

2006

Furrer, R., Genton, M. G. and Nychka, D. (2006). Covariance Tapering for Interpolation of Large Spatial Datasets. Journal of Computational and Graphical Statistics 15(3), 502-523. [Abstract] [BibTeX] [precipitation dataset, "read me"]

Abstract: Interpolation of a spatially correlated random process is used in many scientific areas. The best unbiased linear predictor, often called a kriging predictor in geostatistical science, requires the solution of a (possibly large) linear system based on the covariance matrix of the observations. In this article, we show that tapering the correct covariance matrix with an appropriate compactly supported positive definite function reduces the computational burden significantly and still leads to an asymptotically optimal mean squared error. The effect of tapering is to create a sparse approximate linear system that can then be solved using sparse matrix algorithms. Monte Carlo simulations support the theoretical results. An application to a large climatological precipitation dataset is presented as a concrete and practical illustration.

Keywords: asymptotic optimality, compactly supported covariance, kriging, large linear systems, sparse matrix.

BibTeX:

 @ARTICLE{Furr:Gent:Nych:06,
    AUTHOR = {R. Furrer and M. G. Genton and D. Nychka},
     TITLE = {Covariance Tapering for Interpolation of Large Spatial Datasets},
      YEAR = {2006},	
   JOURNAL = {J. Comput. Graph. Stat.},
  FJOURNAL = {Journal of Computational and Graphical Statistics},
    VOLUME = {15},
    NUMBER = {3},
     PAGES = {502-523},
}

Feingold, G., Furrer, R., Pilewskie, P., Remer L. A., Min, Q. and Jonsson H. (2006). Aerosol Indirect Effect Studies at Southern Great Plains during the May 2003 Intensive Operation Period. Journal of Geophysical Research. 111, D05S14, doi:10.1029/2004JD005648. [Abstract] [BibTeX]

Abstract: During May 2003 the Department of Energy's Atmospheric Radiation Measurement Program conducted an Intensive Operations Period (IOP) to measure the radiative effects of aerosol and clouds. A suite of both in situ and remote sensing measurements were available to measure aerosol and cloud parameters. This paper has three main goals: First, it focuses on comparison between in situ retrievals of the radiatively important drop effective radius r_e and various satellite, airborne, and surface remote sensing retrievals of the same parameter. On 17 May 2003, there was a fortuitous, near-simultaneous sampling of a stratus cloud by five different methods. The retrievals of r_e agree with one another to within ~20%, which is approximately the error estimate for most methods. Second, a methodology for deriving a best estimate of r_e from these different instruments, with their different physical properties and sampling volumes, is proposed and applied to the 17 May event. Third, the paper examines the response of r_e to changes in aerosol on 3 days during the experiment and examines the consistency of remote sensing and in situ measurements of the effect of aerosol on r_e. It is shown that in spite of the generally good agreement in derived r_e, the magnitude of the response of r_e to changes in aerosol is quite sensitive to the method of retrieving r_e and to the aerosol proxy for cloud condensation nuclei. Nonphysical responses are sometimes noted, and it is suggested that further work needs to be done to refine these techniques.

BibTeX:

@ARTICLE{Fein:Furr:Pile:Reme:Min:Jons:07,
    AUTHOR = {Feingold, G. and Furrer, R. and Pilewskie, P. and Remer, L. A. and Min, Q. and Jonsson, H.},
      YEAR = {2006},
     TITLE = {Aerosol Indirect Effect Studies at Southern Great Plains during the May 2003 Intensive Operation Period},
   JOURNAL = {J. Geophys. Res.},
  FJOURNAL = {Journal of Geophysical Research},
    VOLUME = {111},
     PAGES = {D05S14},
       DOI = {10.1029/2004JD005648},
}

Plagellat, C., Kupper, T., Furrer, R., de Alencastro, L. F., Grandjean, D. and Tarradellas, J. (2006). Concentrations and Specific Loads of UV Filters in Sewage Sludge Originating from a Monitoring Network in Switzerland. Chemosphere, 62, 915-925, doi:10.1016/j.chemosphere.2005.05.024. [Abstract] [BibTeX]

Abstract: Many substances related to human activities end up in wastewater and accumulate in sewage sludge. The present study focuses on the analysis of widely used UV filters 3-(4-methylbenzylidene) camphor (4-MBC), octyl-methoxycinnamate (OMC), octocrylene (OC) and octyl-triazone (OT) in sewage sludge originating from a monitoring network in Switzerland. Mean concentrations in stabilised sludge from 14 wastewater treatment plants were 1780, 110, 4840 and 5510 lg/kg dry matter for 4-MBC, OMC, OC and OT, respectively. Specific loads in sewage sludge show that UV filters originate mainly from private households, but surface runoff and industries may be considered as additional sources. This indicates that besides use for sunscreens and cosmetics UV filters might occur in plastics and other materials and be released to the environment by volatilization or leaching. Differences between the modeled per capita loads of UV filters in sewage sludge and the observed specific loads in sewage sludge are probably due to erroneous figures of production volumes, degradation and sorption during wastewater treatment as well as degradation processes during transport in the sewer or sludge treatment. Thus, further research is needed to elucidate the fate of UV filters after application and release into the environment. Other compounds used as UV filters should be included in future studies.

Keywords: Chemical analysis; Sources; Wastewater treatment plant; Sunscreen agents; UV screens; Personal care products

BibTeX:

@ARTICLE{Plag:Kupp:Furr:deAl:Gran:Tarr:06,
    AUTHOR = "C\'ecile Plagellat and Thomas Kupper and Reinhard Furrer and Luiz Felippe de Alencastro and Dominique Grandjean and Joseph Tarradellas",
     TITLE = "Concentrations and specific loads of UV filters in sewage sludge originating from a monitoring network in Switzerland",
   JOURNAL = "Chemosphere",
  FJOURNAL = "Chemosphere", 
    VOLUME = "62",
    NUMBER = "6",
     PAGES = "915-925",
      YEAR = "2006", 
       DOI = "10.1016/j.chemosphere.2005.05.024",
      PMID = {15996716},
}

2005

Fournier, B. and Furrer, R. (2005). Automatic Mapping in the Presence of Substitutive Errors: A Robust Kriging Approach. Extended Abstract in Automatic mapping algorithms for routine and emergency monitoring data. Report on the Spatial Interpolation Comparison (SIC2004) exercise, Dubois, G. ed. Office for Official Publications of the European Communities, Luxembourg, EUR 21595 EN, ISBN: 92-894-9400-X.

Fournier, B. and Furrer, R. (2005). Automatic Mapping in the Presence of Substitutive Errors: A Robust Kriging Approach. Applied GIS 1(2), doi:10.2104/ag050012. [Abstract] [BibTeX]

Abstract: Interpolation of a spatially correlated random process is used in many scientific domains. The best unbiased linear predictor (BLUP), often called kriging predictor in geostatistical science, is sensitive to outliers. The literature contains a few attempts to robustify the kriging predictor, however none of them is completely satisfactory. In this article, we present a new robust linear predictor for a substitutive error model. First, we derive a BLUP, which is computationally very expensive even for moderate sample sizes. A forward search type algorithm is used to derive the predictor resulting in a linear likelihood-weighted mean procedure that is robust with respect to substitutive errors. Monte Carlo simulations support the theoretical results. The new predictor is applied to the two SIC2004 data sets and is evaluated with respect to automatic interpolation and monitoring.

BibTeX:

@ARTICLE{Four:Furr:05a,
    AUTHOR = {Fournier, B. and Furrer, R.},
      YEAR = {2005},
     TITLE = {Automatic Mapping in the Presence of Substitutive Errors: A Robust Kriging Approach},
   JOURNAL = {Applied GIS},
  FJOURNAL = {Applied GIS},
    VOLUME = {1},
    NUMBER = {2},
       DOI = {10.2104/ag050012},  
}

Brändli, R., Kupper, T., Bucheli, T. D., Furrer, R., Stadelmann, F. X. and Tarradellas, J. (2005). Persistent Organic Pollutants in Compost and its Input Materials - A Review of Field Studies. Journal of Environmental Quality 34(3), 735-760, doi:10.2134/jeq2004.0333. [Abstract] [BibTeX]

Abstract: Received for publication August 27, 2004. Composting and the application of compost to the soil follow the principle of recycling and sustainability. Compost can also have a positive effect on physical, chemical, and biological soil parameters. However, little is known about the origin, concentration, and transformation of persistent organic pollutants (POPs) in compost. We therefore compiled literature data on some priority POPs in compost and its main feedstock materials from more than 60 reports. Our data evaluation suggests the following findings. First, median concentrations of {Sigma} 16 polycyclic aromatic hydrocarbons (PAHs), {Sigma} 6 polychlorinated biphenyls (PCBs), and {Sigma} 17 polychlorinated dibenzo-p-dioxins and -furans (PCDD/Fs) were higher in green waste (1803, 15.6 µg/kg dry wt., and 2.5 ng international toxicity equivalent [I-TEQ]/kg dry wt.) than in organic household waste (635, 14.6 µg/kg dry wt., and 2.2 ng I-TEQ/kg dry wt.) and kitchen waste (not available [NA], 14.9 µg/kg dry wt., 0.4 ng I-TEQ/kg dry wt.). The POP concentrations in foliage were up to 12 times higher than in other feedstock materials. Second, in contrast, compost from organic household waste and green waste contained similar amounts of {Sigma} 16 PAHs, {Sigma} 6 PCBs, and {Sigma} 17 PCDD/Fs (1915, 39.8 µg/kg dry wt., and 9.5 ng I-TEQ/kg dry wt., and 1715, 30.6 µg/kg dry wt., and 8.5 ng I-TEQ/kg dry wt., respectively). Third, concentrations of three-ring PAHs were reduced during the composting process, whereas five- to six-ring PAHs and {Sigma} 6 PCBs increased by roughly a factor of two due to mass reduction during composting. {Sigma} 17 PCDD/Fs had accumulated by up to a factor of 14. Fourth, urban feedstock and compost had higher POP concentrations than rural material. Fifth, the highest concentrations of POPs were usually observed in summer samples. Finally, median compost concentrations of POPs were greater by up to one order of magnitude than in arable soils, as the primary recipients of compost, but were well within the range of many urban soils. In conclusion, this work provides a basis for the further improvement of composting and for future risk assessments of compost application.

BibTeX:

@ARTICLE{Brae:Kupp:Buch:Furr:Stad:Tarr:05,
    AUTHOR = {Rahel C. Br\"andli and Thomas D. Bucheli and Thomas Kupper and Reinhard Furrer and Franz X. Stadelmann and Joseph Tarradellas},
      YEAR = {2005},
     TITLE = {Persistent Organic Pollutants in Source-Separated Compost and Its Feedstock Materials—A Review of Field Studies},
   JOURNAL = {J. Environ. Qual.},
  FJOURNAL = {Journal of Environmental Quality},
    VOLUME = {34},
     PAGES = {735-760},
       DOI = {10.2134/jeq2004.0333},  
      PMID = {15843638},
}

Furrer, R. (2005). Covariance Estimation under Spatial Dependence. Journal of Multivariate Analysis, 94(2), 366-381, doi:10.1016/j.jmva.2004.05.009. [Abstract] [BibTeX]

Abstract:

BibTeX:

@ARTICLE{Furr:05,
    AUTHOR = {Furrer, R.},
      YEAR = {2005},
     TITLE = {Covariance Estimation under Spatial Dependence},
   JOURNAL = {J. Multivariate Anal.},
  FJOURNAL = {Journal of Multivariate Analysis},
    VOLUME = {94},
    NUMBER = {2},
     PAGES = {366-381},
       DOI = {10.1016/j.jmva.2004.05.009},  
}

2004

Sain, S. R. and Furrer, R. (2004). Fitting Large-Scale Spatial Models with Applications to Microarray Data Analysis. Computing Science and Statistics (Proceedings of Interface 2004: Computational Biology and Bioinformatics), 36, 869--883. [Abstract] [BibTeX]

Abstract: Many problems in the environmental and biological sciences involve the analysis of large quantities of data. Further, the data in these problems are often subject to various types of structure and, in particular, spatial dependence. Traditional model fitting often fails due to the size of the datasets since it is difficult to not only specify but also to compute with the full covariance matrix. For example, a single microarray can include over 400,000 individual observations. We propose using a very general type of mixed model that has a random spatial component. Recognizing that spatial covariance matrices often exhibit a large number of zero or near-zero entries, covariance tapering is used to force near-zero entries to zero. Then, taking advantage of the sparse nature of such tapered covariance matrices, backfitting is used to estimate the fixed and random model parameters. Results will be demonstrated on a experiment using microarrays to build a profile of differentially expressed genes relating to cerebral vascular malformations, an important cause of hemorrhagic stroke and seizures.

Keywords: Mixed effects; Backfitting; Covariance Tapering; Sparse matrices.

BibTeX:

@INPROCEEDINGS{Sain:Furr:04,
     AUTHOR = {S. R. Sain and R. Furrer},
      title = {Fitting Large-Scale Spatial Models with Applications to Microarray Data Analysis},
  BOOKTITLE = {Proceedings Interface 2004},
   FJOURNAL = {Computing Science and Statistics},
       YEAR = {2004},
     VOLUME = {36},
      PAGES = {869--883},
        URL = {http://www.interfacesymposia.org/I04/I2004Proceedings/SainStephan/SainStephan.paper.pdf}
 }

Kupper, T., Berset, J. D., Etter-Holzer, R., Furrer, R. and Tarradellas, J. (2004). Concentrations and Specific Loads of Polycyclic Musks in Sewage Sludge Originating from a Monitoring Network in Switzerland. Chemosphere, 54(8), 1111-1120, doi:10.1016/j.chemosphere.2003.09.023. [Abstract] [BibTeX]

Abstract:

BibTeX:

@ARTICLE{Kupp:Bers:Ette:Furr:Tarr:04,
  AUTHOR = "T. Kupper and J. D. Berset and R. Etter-Holzer and R. Furrer and J. Tarradellas",
   TITLE = "Concentrations and specific loads of polycyclic musks in sewage sludge originating from a monitoring network in {S}witzerland",
 JOURNAL = "Chemosphere",
FJOURNAL = "Chemosphere",
  VOLUME = "54",
  NUMBER = "8",
   PAGES = "1111-1120",
    YEAR = "2004",
     DOI = "10.1016/j.chemosphere.2003.09.023",
    PMID = {14664839},
}

2003

Fournier, B., Furrer, R., Gsponer, T. and Restle, E.-M. (2003), Editors. Proceedings of the 13th European Young Statisticans Meeting, September 21-26, Ovronnaz, Switzerland, Stämpfli AG, ISBN 3-908152-17-8.

Naveau, P., Furrer, R. and Keckhut, P. (2003). The spatio-temporal influence of the vortex on Artic Total Column Ozone variability, in The ISI International Conference on Environmental Statistics and Health, Mateu, J., Holland, D. González-Manteiga, W. (eds), 131-140. [Abstract]

Genton, M. G. and Furrer, R. (2003). Analysis of Rainfall Data by Simple Good Sense: is Spatial Statistics Worth the Trouble?, in Mapping radioactivity in the environment - Spatial Interpolation Comparison 97, Dubois, G., Malczewski, J., and De Cort M. (eds), 45-50. [Abstract]

Genton, M. G. and Furrer, R. (2003). Analysis of Rainfall Data by Robust Spatial Statistics using S+SpatialStats, in Mapping radioactivity in the environment - Spatial Interpolation Comparison 97, G. Dubois, J. Malczewski, M. De Cort (eds), 118-129. [Abstract]

2002

Furrer, R. (2002). M-Estimation for Dependent Random Variables. Statistics and Probabability Letters, 57(4), 337-341, doi:10.1016/S0167-7152(02)00084-6. [Abstract] [BibTeX]

BibTeX:

@ARTICLE{Furr:02b,
  AUTHOR = "Reinhard Furrer",
   TITLE = "M-Estimation for dependent random variables",
 JOURNAL = "Statist. Probab. Lett.",
FJOURNAL = "Statistics & Probability Letters",
  VOLUME = "57",
  NUMBER = "4",
   PAGES = "337-341",
    YEAR = "2002",
     DOI = "10.1016/S0167-7152(02)00084-6",
}

Furrer, R. (2002). Aspects of Modern Geostatistics: Nonstationarity, Covariance Estimation and State-Space Decompositions. Doctoral thesis under the supervision of Prof. Stephan Morgenthaler. [Abstract] [BibTeX]

Abstract:

BibTeX:

@PHDTHESIS{Furr:02,
  AUTHOR = {R. Furrer},
   TITLE = {Aspects of Modern Geostatistics: Nonstationarity, Covariance Estimation and State-Space Decompositions},
  SCHOOL = {Swiss Federal Insitute of Technology},
    YEAR = {2002},
}

2001

Furrer, R. (2001). Observation-State Representation of Non Stationary Spatial Processes. Proceedings of the 12th European Young Statisticians Meeting, Jánska Dolina, Slovakia, 15.

Furrer, R. (2001). Non Parametric Estimation within Decomposed Spatial Processes. Proceedings of the International Conference of the Royal Statistical Society (RSS2001), University of Glasgow, Scotland, 51.

2000

Furrer, R. (2000). On the Implementation of the Decomposition of Spatial Processes in Matlab. Computing Science and Statistics. Vol. 32, 64-77. [Abstract]

1999

Furrer, R. (1999). Covariance Estimation under Spatial Dependence. Proceedings in Spatial Temporal Modelling and its Applictions. Edited by Mardia, K. V., Aykroyd, R. G. and Dryden, I. L. Leeds University Press, Leeds, 137-140. [Abstract]

Furrer, R. and Genton, M. G. (1999). Robust Spatial Data Analysis of Lake Geneva Sediments with S+SpatialStats. Systems Research and Information Science, Special Issue on Spatial Data: Neural Nets/Statistics, 8(4), 257-272. [Abstract] [BibTeX]

Abstract: This paper discusses the use of robust geostatistical methods on a multivariate data set of sediments in the Lake Geneva in Switzerland. Each variable is detrended via nonparametric estimation penalized with a smoothing parameter. The optimal trend is computed with a smoothing parameter based on cross-validation. Then, variograms are estimated by a highly robust estimator of scale. The parametric variogram models are fitted by generalized least squares, thus taking account of the variance-covariance structure of the variogram estimates. Kriging has been performed inside the Lake Geneva boundaries, and results are in close agreements with the geographical surroundings. The comparison of the kriging results with and without detrending the data relieved the importance of the trend detection and tren d removing, and that a simple model with constant trend for this data set is not satisfactory. All these computations are done with the software {\sc S+SpatialStats}, extended with new functions in {\sc S+} that are made available.

BibTeX:

@ARTICLE{Furr:Gent:99,
  AUTHOR = 	 {Furrer, R. and Genton, M. G.},
  TITLE = 	 {Robust Spatial Data Analysis of Lake Geneva Sediments with S+SpatialStats},
  JOURNAL = 	 {Syst. Res. Inform. Sci.},
  FJOURNAL = 	 {Systems Research and Information Science},
  YEAR = 	 {1999},
  VOLUME = 	 {8},
  NUMBER = 	 {4},
  PAGES = 	 {257--272},
  OPTannote = 	 {Special Issue on Spatial Data: Neural Nets/Statistics}
}

1998

Furrer, R. (1998). Principal Component Analysis of Lake Geneva Sediments. Proceedings of the Fourth Annual Conference of the International Association for Mathematical Geology . Edited by, Buccianti, A., Nardi, G. and Potenza, R., De Frede Editore, Napoli, 421-426. [Abstract]

Genton, M. G. and Furrer, R. (1998). Analysis of Rainfall Data by Robust Spatial Statistics using S+SpatialStats. Journal of Geographic Information and Decision Analysis, Vol. 2, No. 2, 126-136. [Abstract] [BibTeX]

BibTeX:

@ARTICLE{Gent:Furr:98b,
  AUTHOR =       "M. G. Genton and R. Furrer",
  TITLE =        "Analysis of Rainfall Data by Robust Spatial Statistics using {S+SpatialStats}",
  JOURNAL =      "Journal of Geographic Information and Decision Analysis",
  VOLUME =       "2",
  YEAR =         "1998",
  NUMBER =       "2",
  PAGES =        "126--136",
}

Genton, M. G. and Furrer, R. (1998). Analysis of Rainfall Data by Simple Good Sense: is Spatial Statistics Worth the Trouble?. Journal of Geographic Information and Decision Analysis, Vol. 2, No. 2, 11-17. [Abstract] [BibTeX]

BibTeX:

@ARTICLE{Gent:Furr:98a,
  AUTHOR =       "M. G. Genton and R. Furrer",
  TITLE =        "Analysis of Rainfall Data by Simple Good Sense: Is Spatial Statistics Worth the Trouble?",
  JOURNAL =      "Journal of Geographic Information and Decision Analysis",
  VOLUME =       "2",
  YEAR =         "1998",
  NUMBER =       "2",
  PAGES =        "11--17",
}

Last modified Feb 6 2024 by reinhard. furrer @ math. uzh. ch