randomgen.generator.ExtendedGenerator.standard_wishart¶

ExtendedGenerator.standard_wishart(df, dim, size=None, rescale=True)¶

Draw samples from the Standard Wishart and Pseudo-Wishart distributions

Parameters:¶

df¶

The degree-of-freedom for the simulated Wishart variates.

dim¶

The dimension of the simulated Wishart variates.

size=None¶

Output shape, excluding trailing dims. If the given shape is, e.g., (m, n, k), then m * n * k samples are drawn, each with shape (dim, dim). The output then has shape (m, n, k, dim, dim). Default is None, in which case a single value with shape (dim, dim) is returned.

rescale=True¶

Flag indicating whether to rescale the outputs to have expectation identity. The default is True. If rescale is False, then the expected value of the generated variates is df * eye(dim).

Returns:¶

The generated variates from the standard wishart distribution.

Return type:¶

numpy.ndarray

See also

wishart

Generate variates with a non-identify scale. Also support array inputs for df.

Notes

Uses the method of Odell and Feiveson [1] when df >= dim. Otherwise variates are directly generated as the inner product of df by dim arrays of standard normal random variates. See [1], [2], and [3] for more information.

References