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Directional (version 6.8)

Simulation of random values from a spherical Kent distribution: 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)

Value

A matrix with the simulated data.

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, \(\beta\).

Author

Michail Tsagris.

R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.

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.

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

Run this code
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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