Directional (version 4.0)

Angular central Gaussian random values simulation: 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 \(R^d\).

Value

A matrix with the simulated data.

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.

References

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

See Also

acg, rvmf, rvonmises

Examples

# NOT RUN {
s <- cov( iris[, 1:4] )
x <- racg(100, s)
acg(x)  
vmf(x)  ## the concentration parameter, kappa, is very low, close to zero, as expected.
# }