R: Probability density function for multivariate t

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 Index]