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.

References