dmvnorm {emdbook} | R Documentation |
Multivariate normal distribution density function
Description
Calculates the probability density function of the multivariate normal distribution
Usage
dmvnorm(x, mu, Sigma, log = FALSE, tol = 1e-06)
Arguments
x |
a vector or matrix of multivariate observations |
mu |
a vector or matrix of mean values |
Sigma |
a square variance-covariance matrix |
log |
(logical) return log-likelihood? |
tol |
tolerance for positive definiteness |
Details
uses naive linear algebra – could probably use QR decomposition and/or crossprod.
Value
vector of log-likelihoods
Author(s)
Ben Bolker
See Also
mvrnorm
(in MASS
package),
dmvnorm
(in mvtnorm
package)
Examples
M = matrix(c(1,0.5,0.5,0.5,1,0.5,0.5,0.5,1),nrow=3)
dmvnorm(1:3,mu=1:3,Sigma=M,log=TRUE)
dmvnorm(matrix(1:6,nrow=2),mu=1:3,Sigma=M,log=TRUE)
dmvnorm(matrix(1:6,nrow=2),mu=matrix(1:6,nrow=2),Sigma=M,log=TRUE)
[Package emdbook version 1.3.13 Index]