rbingham: Simulation of random values from a Bingham distribution with...
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View source: R/random_values_simulation.R
Simulation of random values from a Bingham distribution with any symmetric matrix R Documentation
Simulation of random values from a Bingham distribution with any symmetric matrix
Description
Simulation of random values from a Bingham distribution with any symmetric matrix.
Usage
rbingham(n, A)
Arguments
n
Sample size.
A
A symmetric matrix.
Details
The eigenvalues of the q x q symmetric matrix A are calculated and the smallest of
them is subtracted from the rest. The q - 1 non zero eiqenvalues are then passed to
rbing. The generated data are then right multiplied by V^T, where
V is the matrix of eigenvectors of the matrix A.
Value
A matrix with the simulated data.
Author(s)
Michail Tsagris
R implementation and documentation: Michail Tsagris <mtsagris@uoc.gr> and
Manos Papadakis <papadakm95@gmail.com>
References
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
C.J. Fallaize and T. Kypraios (2014).
Exact Bayesian Inference for the Bingham Distribution.
Statistics and Computing (No volum assigned yet).
http://arxiv.org/pdf/1401.2894v1.pdf
See Also
rvmf
Examples
A <- cov( iris[, 1:4] )
x <- rbingham(100, A)
x
Rfast documentation built on Nov. 9, 2023, 5:06 p.m.
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View source: R/random_values_simulation.R
| Simulation of random values from a Bingham distribution with any symmetric matrix | R Documentation |
Simulation of random values from a Bingham distribution with any symmetric matrix
Description
Simulation of random values from a Bingham distribution with any symmetric matrix.
Usage
rbingham(n, A)
Arguments
n |
Sample size. |
A |
A symmetric matrix. |
Details
The eigenvalues of the q x q symmetric matrix A are calculated and the smallest of
them is subtracted from the rest. The q - 1 non zero eiqenvalues are then passed to
rbing. The generated data are then right multiplied by V^T, where
V is the matrix of eigenvectors of the matrix A.
Value
A matrix with the simulated data.
Author(s)
Michail Tsagris
R implementation and documentation: Michail Tsagris <mtsagris@uoc.gr> and Manos Papadakis <papadakm95@gmail.com>
References
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
C.J. Fallaize and T. Kypraios (2014). Exact Bayesian Inference for the Bingham Distribution. Statistics and Computing (No volum assigned yet). http://arxiv.org/pdf/1401.2894v1.pdf
See Also
rvmf
Examples
A <- cov( iris[, 1:4] )
x <- rbingham(100, A)
x
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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