Angular central Gaussian random values simulation
Angular central Gaussian random values simulation.
racg(n, sigma)
n |
The sample size, a numerical value. |
sigma |
The covariance matrix in R^d. |
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.
A matrix with the simulated data.
Michail Tsagris.
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.
Tyler D. E. (1987). Statistical analysis for the angular central Gaussian distribution on the sphere. Biometrika 74(3): 579-589.
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.
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