| covapprox.error {KriSp} | R Documentation |
Evaluates different error measures of the linear covariance approximation used in the kriging approach
covapprox.error(n, cov.fun='expo.cov', cov.fun.args=list(range=1),
taper.fun='spher.cov', taper.fun.args=list(range=1),
hmax=taper.fun.args$range,nres=25)
n |
Number of knots to evaluate the approximation |
cov.fun |
Covariance function in the form of an R function, or its name as a string. |
cov.fun.args |
A list with the arguments to call the covariance function (in addition to the locations). |
taper.fun |
Taper function in the form of an R function, or its name as a string. |
taper.fun.args |
A list with the arguments to call the taper function (in addition to the locations). |
hmax |
Distance over which the error is calculated. |
nres |
Resolution over which the errors are calculated. |
n=1000 usually gives a maximum error smaller than 0.1
percent of the total sill.
A list with the elements:
max |
Maximum of the error. |
ise |
Approximation of the integrated squared error. |
iae |
Approximation of the integrated absolute error. |
covapprox |
Linear approximation of the covariance. |
error |
Error committed using the linear interpolation. |
To obtain a `small' tapering effect, the taper range
can be set to a large value. In such a case, hmax should
be set to the diameter of the domain.
Using the tophat function as taper, no tapering
is done.
Covariance functions such as expo.cov,
mater.cov, etc.
Krig.sparse and
Krig.simple.sparse.
# plot the error using the default functions.
nres <- 10
n <- 25
h <- seq(0,to=1, l=n*nres)
plot( h, covapprox.error(n,nres=nres)$error, type='l')
# evaluate error for a covariance only.
expoapprox <- covapprox.error(1000,taper.fun=tophat,
taper.fun.args=list(range=5))
# all values are negative, as expo.cov is convex.