dmt: Probability density function for multivariate t

In LearnBayes: Functions for Learning Bayesian Inference

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)

LearnBayes documentation built on May 1, 2019, 7:03 p.m.