R: Multivariate normal and t random values simulation

Multivariate normal and t random values simulation {Rfast} | R Documentation

## Multivariate normal and t random values simulation

### Description

Multivariate normal and t random values simulation.

### Usage

    rmvnorm(n, mu, sigma)
    rmvt(n, mu, sigma, v)

### Arguments

`n` | The sample size, a numerical value.
`mu` | The mean vector in R^d.
`sigma` | The covariance matrix in R^d.
`v` | The degrees of freedom.

### Details

The algorithm uses univariate normal random values and transforms them to multivariate via a spectral decomposition. It is faster than the command "mvrnorm" available from MASS, and it allows for singular covariance matrices.

### Value

A matrix with the simulated data.

### Author(s)

Michail Tsagris

R implementation and documentation: Michail Tsagris <mtsagris@yahoo.gr>

### References

Aitchison J. (1986). The statistical analysis of compositional data. Chapman & Hall.

### See Also

`racg, rmvlaplace, rmvt`

### Examples

    x <- as.matrix(iris[, 1:4])
    m <- colmeans(x)
    s <- cov(x)
    y <- rmvnorm(1000, m, s)
    res<-colmeans(y)
    res<-cov(y)
    y <- NULL

[Package Rfast version 2.0.0 Index]