RRgauss: Vector Of Independent Gaussian Random Variables

Description Usage Arguments Details Value See Also Examples

View source: R/RMmodels.R

Description

RRgauss defines the d-dimensional vector of independent Gaussian random variables.

Usage

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RRgauss(mu, sd, log) 

Arguments

mu, sd, log

see Normal. Here, the components can be vectors, leading to multivariate distibution with independent components.

Details

It has the same effect as RRdistr(norm(mu=mu, sd=sd, log=log)).

Value

RRgauss returns an object of class RMmodel.

See Also

RMmodel, RRdistr, RRunif.

Do not mix up RRgauss with RMgauss or RPgauss.

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
r <- RFrdistr(RRgauss(mu=c(1,5)), n=1000, dim=2)
plot(r[1,], r[2, ])

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