RRgauss: Vector Of Independent Gaussian Random Variables

In RandomFields: Simulation and Analysis of Random Fields

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.

See Also

RMmodel, RRdistr, RRunif.

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