Simulation of random values from a spherical Kent distribution {Directional}

Simulation of random values from a spherical Kent distribution

Description

Simulation of random values from a spherical Kent distribution.

Usage

rkent(n, k, m, b)

Arguments

n

The sample size.

k

The concentraion parameter \kappa. It has to be greater than 0.

m

The mean direction (Fisher part).

b

The ovalness parameter, \beta.

Details

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.

Value

A matrix with the simulated data.

Author(s)

Michail Tsagris.

R implementation and documentation: Michail Tsagris [e-mail].

References

Kent J. T., Ganeiber A. M. and Mardia K. V. (2018). A new unified approach for the simulation of a wide class of directional distributions. Journal of Computational and Graphical Statistics, 27(2): 291–301.

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

See Also

rfb, rbingham, rvmf, f.rbing

Examples

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)