The Multivariate Normal Distribution

Description

Density and random generation for Multivariate Normal distributions with mean vector mean, and covariance matrix cov.

Usage

ddmvn(dat,n, p, mean, cov)
rdmvn(    n, p, mean, cov)

Arguments

Value

ddmvn gives the density values; rdmvn generates the random numbers

See Also

rdemmix,ddmvt,ddmsn, ddmst,rdmvt,rdmsn, rdmst.

Examples

n <- 100
p <- 2

mean <- rep(0,p)
cov  <- diag(p)

set.seed(3214)

y <-   rdmvn(  n,p,mean,cov)

den <- ddmvn(y,n,p,mean,cov)

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(EMMIXskew)
Loading required package: lattice
Loading required package: mvtnorm
Loading required package: KernSmooth
KernSmooth 2.23 loaded
Copyright M. P. Wand 1997-2009
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/EMMIXskew/ddmvn.Rd_%03d_medium.png", width=480, height=480)
> ### Name: ddmvn
> ### Title: The Multivariate Normal Distribution
> ### Aliases: ddmvn rdmvn
> ### Keywords: cluster datasets
> 
> ### ** Examples
> 
> n <- 100
> p <- 2
> 
> mean <- rep(0,p)
> cov  <- diag(p)
> 
> set.seed(3214)
> 
> y <-   rdmvn(  n,p,mean,cov)
> 
> den <- ddmvn(y,n,p,mean,cov)
> 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>