ks (version 1.8.11)

dmvnorm.mixt: Multivariate and univariate normal mixture distribution

Description

Random generation and density values from normal mixture distribution.

Usage

dmvnorm.mixt(x, mus, Sigmas, props)
rmvnorm.mixt(n=100, mus=c(0,0), Sigmas=diag(2), props=1, mixt.label=FALSE)
dnorm.mixt(x, mus=0, sigmas=1, props=1)
rnorm.mixt(n=100, mus=0, sigmas=1, props=1, mixt.label=FALSE)

Arguments

n

number of random variates

x

matrix of quantiles

mus

(stacked) matrix of mean vectors (>1-d) or vector of means (1-d)

Sigmas

(stacked) matrix of variance matrices (>1-d)

sigmas

vector of standard deviations (1-d)

props

vector of mixing proportions

mixt.label

flag to output numeric label indicating mixture component. Default is FALSE.

Value

• Normal mixture random vectors and density values.

Details

rmvnorm.mixt and dmvnorm.mixt are based on the rmvnorm and dmvnorm functions from the mvtnorm library.

See Also

rmvt.mixt, dmvt.mixt, dnorm.mixt, rnorm.mixt

Examples

## bivariate 
mus <- rbind(c(-3/2,0), c(3/2,0))
Sigmas <- rbind(diag(c(1/16, 1)), rbind(c(1/16, 1/18), c(1/18, 1/16)))
props <- c(2/3, 1/3)
x <- rmvnorm.mixt(1000, mus, Sigmas, props)
dens <- dmvnorm.mixt(x, mus, Sigmas, props)

##univariate
x <- rnorm.mixt(1000, mus=c(-1,1), sigmas=c(0.5, 0.5), props=c(1/2, 1/2))
dens <- dnorm.mixt(x, mus=c(-1,1), sigmas=c(0.5, 0.5), props=c(1/2, 1/2))