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It simulates random values from a Bingham distribution with any given symmetric matrix.
rbingham(n, A)A matrix with the siumlated data.
The sample size.
A symmetric matrix.
Michail Tsagris.
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.
The eigenvalues are fist calcualted and then Chris Fallaize and Theo Kypraio's code (f.rbing) is used. The resulting simulated data anre then right multiplied by the eigenvectors of the matrix A.
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
Fallaize C. J. and Kypraios T. (2016). Exact bayesian inference for the Bingham distribution. Statistics and Computing, 26(1): 349--360. http://arxiv.org/pdf/1401.2894v1.pdf
f.rbing, rfb, rvmf, rkent
A <- cov(iris[, 1:3])
x <- rbingham(100, A)
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