spam (version 1.4-0)

covmat: Covariance functions

Description

Evaluate a covariance function.

Usage

covmat(h, theta, ... , type="sph")
cov.exp(h, theta, ... , eps= .Spam$eps)
cov.sph(h, theta, ... , eps= .Spam$eps)
cov.nug(h, theta, ... , eps= .Spam$eps)
cov.wu1(h, theta, ... , eps= .Spam$eps)
cov.wu2(h, theta, ... , eps= .Spam$eps)
cov.wu3(h, theta, ... , eps= .Spam$eps)
cov.wend1(h, theta, ... , eps= .Spam$eps)
cov.wend2(h, theta, ... , eps= .Spam$eps)
cov.mat(h, theta, ... , eps= .Spam$eps)

Arguments

h

object containing the lags.

theta

parameter of the covariance function, see ‘Details’.

type

covariance function specification.

…

arguments passed from other methods.

eps

tolerance level.

Value

Covariance function evaluated on h.

Details

covmat is a wrapper that calls the other functions according to the argument type. The nomenclature is similar to premat

The parametrization is (range, sill, [smoothness], nugget), where only the range needs to be specified. Default values are (1,[1],0). In case of negative parameter values, a warning is issued and the absolute value is retained. Although more cryptic, having all arguments as a single vector simplifies optimization with optim.

Currently, the functions distinguish between a sparse spam object h and any other numeric type. In the future, this might change and appropriate methods will be implemented.

References

Any classical book about geostatistics.

See Also

precmat.

Examples

locs <- cbind(runif(10),runif(10))
h <- nearest.dist(locs, delta=.3)
Sigma <- cov.sph(h, c(.3, 1, .1))


h <- seq(0, to=1, length.out=100)
plot( h, cov.exp(h, c(1/3,1)), type='l', ylim=c(0,1))
type <- c("sph","wendland1","wendland2","wu1","wu2","wu3")
for (i in 1:6) 
  lines( h, covmat(h, 1, type=type[i]), col=i+1)
legend('topright',legend=type, col=2:7, lty=1)