Simulation of random values from a spherical Kent distribution
Simulation of random values from a spherical Kent distribution.
rkent(n, k, m, b)
n |
The sample size. |
k |
The concentraion parameter κ. It has to be greater than 0. |
m |
The mean direction (Fisher part). |
b |
The ovalness parameter, β. |
Random values from a Kent distribution on the sphere are generated. The function generates from a spherical Kent distribution using rfb with an arbitrary mean direction and then rotates the data to have the desired mean direction.
A matrix with the simulated data.
Michail Tsagris
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr and Giorgos Athineou <gioathineou@gmail.com>
Kent J.T., Ganeiber A.M. and Mardia K.V. (2013). A new method to simulate the Bingham and related distributions in directional data analysis with applications. http://arxiv.org/pdf/1310.8110v1.pdf
k <- 15 mu <- rnorm(3) mu <- mu / sqrt( sum(mu^2) ) A <- diag( c(-5, 0, 5) ) x <- rfb(500, k, mu, A) kent.mle(x) y <- rkent(500, k, mu, A[3, 3]) kent.mle(y)
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