dcmvnorm | R Documentation |
Density of a (conditional) multivariate normal variate
dcmvnorm(x, mean = 0, V = 1, keep=1, cond=(1:length(x))[-keep], log=FALSE)
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
Jarrod Hadfield j.hadfield@ed.ac.uk
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
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