R: Density of the multivariate normal and t distributions

Density of the multivariate normal and t distributions {Rfast} | R Documentation

## Density of the multivariate normal and t distributions

### Description

Density of the multivariate normal and t distributions.

### Usage

    dmvnorm(x, mu, sigma, logged = FALSE)
    dmvt(x, mu, sigma, nu, logged = FALSE)

### Arguments

`x` | A numerical matrix with the data. The rows correspond to observations and the columns to variables.
`mu` | The mean vector.
`sigma` | The covariance matrix.
`nu` | The degrees of freedom for the multivariate t distribution.
`logged` | Should the logarithm of the density be returned (TRUE) or not (FALSE)?

### Details

The (log) density of the multivariate normal distribution is calculated for given mean vector and covariance matrix.

### Value

A numerical vector with the density values calculated at each vector (row of the matrix x).

### Author(s)

Michail Tsagris

R implementation and documentation: Michail Tsagris <mtsagris@yahoo.gr> and Manos Papadakis <papadakm95@gmail.com>.

### References

Kanti V. Mardia, John T. Kent and John M. Bibby (1979). Multivariate analysis. Academic Press, London.

### See Also

`rmvnorm, rmvt, mvnorm.mle, iag.mle`

### Examples

    x <- matrnorm(100, 20)
    mu <- colmeans(x)
    s <- cova(x)
    a1 <- dmvnorm(x, mu, s)
    a2 <- dmvt(x, mu, s, 1)
    x <- NULL

[Package Rfast version 2.0.0 Index]