rPsuedoWishart {rWishart} | R Documentation |
Random Psuedo Wishart Matrix
Description
Generate n
random matrices, distributed according to the Wishart distribution with parameters Sigma
and df
, W_p(Sigma, df).
Usage
rPsuedoWishart(n, df, Sigma, covariance = FALSE, simplify = "array")
Arguments
n |
integer: the number of replications. |
df |
numeric parameter, “degrees of freedom”. |
Sigma |
positive definite ( |
covariance |
logical on whether a covariance matrix should be generated |
simplify |
logical or character string; should the result be
simplified to a vector, matrix or higher dimensional array if
possible? For |
Details
If X_1, ..., X_m is a sample of m independent multivariate Gaussians with mean vector 0, and covariance matrix Sigma, the distribution of M = X'X is W_p(Sigma, m).
Value
A numeric array of dimension p * p * n
, where each array is a positive semidefinite matrix, a realization of the Wishart distribution W_p(Sigma, df)
References
Diaz-Garcia, Jose A, Ramon Gutierrez Jaimez, and Kanti V Mardia. 1997. “Wishart and Pseudo-Wishart Distributions and Some Applications to Shape Theory.” Journal of Multivariate Analysis 63 (1): 73–87. doi:10.1006/jmva.1997.1689.
Examples
rPsuedoWishart(2, 5, diag(1, 20))