# dcmvnorm: Density of a (conditional) multivariate normal variate In MCMCglmm: MCMC Generalised Linear Mixed Models

## Description

Density of a (conditional) multivariate normal variate

## Usage

 `1` ```dcmvnorm(x, mean = 0, V = 1, keep=1, cond=(1:length(x))[-keep], log=FALSE) ```

## Arguments

 `x` vector of observations `mean` vector of means `V` covariance matrix `keep` vector of integers: observations for which density is required `cond` vector of integers: observations to condition on `log` if TRUE, density p is given as log(p)

numeric

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16``` ```V1<-cbind(c(1,0.5), c(0.5,1)) dcmvnorm(c(0,2), c(0,0), V=V1, keep=1, cond=2) # density of x=0 conditional on x=2 given # x ~ MVN(c(0,0), V1) dcmvnorm(c(0,2), c(0,0), V=V1, keep=1, cond=NULL) # density of x=0 marginal to x dnorm(0,0,1) # same as univariate density V2<-diag(2) dcmvnorm(c(0,2), c(0,0), V=V2, keep=1, cond=2) # density of x=0 conditional on x=2 given # x ~ MVN(c(0,0), V2) dnorm(0,0,1) # same as univariate density because V2 is diagonal ```

### Example output

```Loading required package: Matrix