RMbernoulli: Covariance Model for binary field based on a Gaussian field

Description Usage Arguments Details Value Note References See Also Examples

View source: R/RMmodels.R

Description

RMbernoulli gives the centered correlation function of a binary field, obtained by thresholding a Gaussian field.

Usage

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RMbernoulli(phi, threshold, correlation, centred, var, scale, Aniso, proj)

Arguments

phi

covariance function of class RMmodel.

threshold

real valued threshold, see RPbernoulli. Currently, only threshold=0.0 is possible.

Default: 0.

correlation

logical. If FALSE the corresponding covariance function is returned.

Default: TRUE.

centred

logical. If FALSE the uncentred covariance is returned.

Default: TRUE.

var,scale,Aniso,proj

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

Details

This model yields the covariance function of the field that is returned by RPbernoulli.

Value

RMbernoulli returns an object of class RMmodel.

Note

Previous to version 3.0.33 the covariance function was returned, not the correlation function.

References

Ballani, Schlather

See Also

RPbernoulli, RMmodel, RFsimulate.

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

threshold <- 0
x <- seq(0, 5, 0.02)
GaussModel <- RMgneiting()

n <- 1000
z <- RFsimulate(RPbernoulli(GaussModel, threshold=threshold), x=x, n=n)
plot(z)

model <- RMbernoulli(RMgauss(), threshold=threshold, correlation=FALSE)
plot(model, xlim=c(0,5))
z1 <- as.matrix(z)
estim.cov <- apply(z1, 1, function(x) cov(x, z1[1,]))
points(coordinates(z), estim.cov, col="red")

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