An expansion of R's 'stats' random wishart matrix generation. This package allows the user to generate singular, Uhlig and Harald (1994) <doi:10.1214/aos/1176325375>, and pseudo wishart, Diaz-Garcia, et al.(1997) <doi:10.1006/jmva.1997.1689>, matrices. In addition the user can generate wishart matrices with fractional degrees of freedom, Adhikari (2008) <doi:10.1061/(ASCE)0733-9399(2008)134:12(1029)>, commonly used in volatility modeling. Users can also use this package to create random covariance matrices.
Generate n
random matrices, distributed according to the Wishart distribution with parameters Sigma
and df
, W_p(Sigma, df).
NonsingularWishart(df, Sigma, covariance = FALSE)
numeric parameter, “degrees of freedom”.
positive definite (\(p\times p\)) “scale” matrix, the matrix parameter of the distribution.
logical on whether a covariance matrix should be generated
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)
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).
# NOT RUN {
NonsingularWishart(20, diag(1,5))
# }
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