Angular central Gaussian random values simulation {Directional}

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 [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, rvmf, rvonmises

Examples

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