# dcmvnorm

From MCMCglmm v2.29
by Jarrod Hadfield

##### Density of a (conditional) multivariate normal variate

Density of a (conditional) multivariate normal variate

- Keywords
- distribution

##### Usage

`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)

##### Value

numeric

##### Examples

```
# NOT RUN {
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[1]=0 conditional on x[2]=2 given
# x ~ MVN(c(0,0), V1)
dcmvnorm(c(0,2), c(0,0), V=V1, keep=1, cond=NULL)
# density of x[1]=0 marginal to x[2]
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[1]=0 conditional on x[2]=2 given
# x ~ MVN(c(0,0), V2)
dnorm(0,0,1)
# same as univariate density because V2 is diagonal
# }
```

*Documentation reproduced from package MCMCglmm, version 2.29, License: GPL (>= 2)*

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