RMexp: Exponential Covariance Model

Description Usage Arguments Details Value References See Also Examples

View source: R/RMmodels.R

Description

RMexp is a stationary isotropic covariance model whose corresponding covariance function only depends on the distance r ≥ 0 between two points and is given by

C(r) = exp(-r).

Usage

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RMexp(var, scale, Aniso, proj)

Arguments

var,scale,Aniso,proj

optional arguments; same meaning for any RMmodel. If not passed, the above covariance function remains unmodified.

Details

This model is a special case of the Whittle covariance model (see RMwhittle) if ν=0.5 and of the symmetric stable family (see RMstable) if ν=1. Moreover, it is the continuous-time analogue of the first order autoregressive time series covariance structure.

The exponential covariance function is a normal scale mixture.

Value

RMexp returns an object of class RMmodel.

References

Covariance model

Tail correlation function

See Also

RMwhittle, RMstable, RMmodel, RFsimulate, RFfit.

Examples

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RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set
##                   RFoptions(seed=NA) to make them all random again

model <- RMexp()
x <- seq(0, 10, 0.02)
plot(model)
plot(RFsimulate(model, x=x))

Example output

Loading required package: sp
Loading required package: RandomFieldsUtils

Attaching package:RandomFieldsThe following object is masked frompackage:RandomFieldsUtils:

    RFoptions

NULL
NOTE: simulation is performed with fixed random seed 0.
Set 'RFoptions(seed=NA)' to make the seed arbitrary.
New output format of RFsimulate: S4 object of class 'RFsp';
for a bare, but faster array format use 'RFoptions(spConform=FALSE)'.

RandomFields documentation built on Jan. 19, 2022, 1:06 a.m.