racg: Angular central Gaussian random values simulation

In Rfast: A Collection of Efficient and Extremely Fast R Functions

Angular central Gaussian random values simulation

Description

Angular central Gaussian random values simulation.

Usage

racg(n, sigma, seed = NULL)

Arguments

n	The sample size, a numerical value.
sigma	The covariance matrix in R^d.
seed	If you want the same to be generated again use a seed for the generator, an integer number.

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 <[e-mail]>

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.

Rfast documentation built on Nov. 9, 2023, 5:06 p.m.