R: Angular central Gaussian random values simulation

Angular central Gaussian random values simulation {Rfast} | R Documentation

## Angular central Gaussian random values simulation

### Description

Angular central Gaussian random values simulation.

### Usage

    racg(n, sigma)

### Arguments

`n` | The sample size, a numerical value.
`sigma` | The covariance matrix in R^d.

### Details

The algorithm uses univariate normal random values and transforms them to multivariate via a spectral decomposition. The vectors are then scaled to have unit length.

### Value

A matrix with the simulated data.

### Author(s)

Michail Tsagris

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

### References

Tyler D. E. (1987). Statistical analysis for the angular central Gaussian distribution on the sphere. Biometrika 74(3): 579-589.

### See Also

`acg.mle, rmvnorm, rmvlaplace, rmvt`

### Examples

    s <- cov( iris[, 1:4] )
    x <- racg(100, s)
    res<-acg.mle(x)
    res<-vmf.mle(x)  ## the concentration parameter, kappa, is very low, close to zero, as expected.

[Package Rfast version 2.0.0 Index]