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RRgauss

Vector Of Independent Gaussian Random Variables

Description

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

Usage

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.

Author(s)

See Also

Do not mix up RRgauss with RMgauss or RPgauss.

Examples

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

Simulation and Analysis of Random Fields

v3.3.10
GPL (>= 3)
Authors
Martin Schlather [aut, cre], Alexander Malinowski [aut], Marco Oesting [aut], Daphne Boecker [aut], Kirstin Strokorb [aut], Sebastian Engelke [aut], Johannes Martini [aut], Felix Ballani [aut], Olga Moreva [aut], Jonas Auel[ctr], Peter Menck [ctr], Sebastian Gross [ctr], Ulrike Ober [ctb], Paulo Ribeiro [ctb], Brian D. Ripley [ctb], Richard Singleton [ctb], Ben Pfaff [ctb], R Core Team [ctb]
Initial release

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