dmt {LearnBayes} | R Documentation |
Probability density function for multivariate t
Description
Computes the density of a multivariate t distribution
Usage
dmt(x, mean = rep(0, d), S, df = Inf, log=FALSE)
Arguments
x |
vector of length d or matrix with d columns, giving the coordinates of points where density is to evaluated |
mean |
numeric vector giving the location parameter of the distribution |
S |
a positive definite matrix representing the scale matrix of the distribution |
df |
degrees of freedom |
log |
a logical value; if TRUE, the logarithm of the density is to be computed |
Value
vector of density values
Author(s)
Jim Albert
Examples
mu <- c(1,12,2)
Sigma <- matrix(c(1,2,0,2,5,0.5,0,0.5,3), 3, 3)
df <- 4
x <- c(2,14,0)
f <- dmt(x, mu, Sigma, df)
[Package LearnBayes version 2.15.1 Index]