RMexp: Exponential Covariance Model
In RandomFields: Simulation and Analysis of Random Fields

Description Usage Arguments Details Value References See Also Examples

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).

1	RMexp(var, scale, Aniso, proj)

var,scale,Aniso,proj

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

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.

RMexp returns an object of class RMmodel.

Covariance model

Gelfand, A. E., Diggle, P., Fuentes, M. and Guttorp, P. (eds.) (2010) Handbook of Spatial Statistics. Boca Raton: Chapman & Hall/CRL.

Tail correlation function

Strokorb, K., Ballani, F., and Schlather, M. (2014) Tail correlation functions of max-stable processes: Construction principles, recovery and diversity of some mixing max-stable processes with identical TCF. Extremes, Submitted.

RMwhittle, RMstable, RMmodel, RFsimulate, RFfit.

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))

Loading required package: sp
Loading required package: RandomFieldsUtils

Attaching package: ‘RandomFields’

The following object is masked from ‘package: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)'.