| covariance {KriSp} | R Documentation |
Computes theoretical covariance function at supplied distance values. Models include exponential, spherical, Matern and compactly supported covariances.
spher.cov(distance, range, sill=1, nugget=0, eps=1.0e-7,...) expo.cov(distance, range, sill=1, nugget=0, effect=FALSE, eps=1.0e-7,...) mater.cov(distance, smooth, range, sill=1, nugget=0, eps=1.0e-7,...) tri.cov(distance, range, sill=1, nugget=0, eps=1.0e-7,...) Wu1.cov(distance, range, sill=1, nugget=0, eps=1.0e-7,...) Wu2.cov(distance, range, sill=1, nugget=0, eps=1.0e-7,...) Wu3.cov(distance, range, sill=1, nugget=0, eps=1.0e-7,...) tophat(distance, range, sill=1,...)
distance |
a vector/matrix of distances to compute the covariance for. |
range |
the range value. |
smooth |
smoothness of the Matern covariance. |
sill |
the partial sill value. The absolute sill (the
variance or equivalently the covariance at distance zero) is
sill + nugget. |
nugget |
the nugget effect. |
effect |
if TRUE, range is the practial range |
eps |
any distance less than it will be set to nugget +
sill. |
... |
see below. |
The tophat is NOT an actual covariance function. It is included for illustration purposes only.
The triangular, spherical and the Wu type functions are compactly supported covariance functions, vanishing beyond the range. The triangular and the first Wu type are not valid in two dimensions and up.
a vector/matrix of covariance values at the supplied distances.
To all the covariance functions the ... argument is added
to ensure compatibility between different types of covariance
functions. Although this would not be necessary, it simplifies
internal coding and usage considerably.
There is a difference between exp.cov and expo.cov, as well as
matern.cov and mater.cov functions in fields and KriSp.
distance <- seq(0,2,length=150) plot( distance, mater.cov(distance,smooth=1,range=.4,sill=.8,nugget=.2))