StudentBVAR.prior_replications#

StudentBVAR.prior_replications(n_replications=200, *, df=None, seed=None)[source]#

Data sets the prior generates, with Student-t innovations.

(B, Sigma) come from the Normal-inverse-Wishart prior as in the conjugate model; the degrees of freedom are the stated value, or – when None, as at fit – one draw per replication from the flat prior on the estimation grid.

Parameters:

  • n_replications (int) – Replicated data sets.

  • df (float | None) – Degrees of freedom, above two, or None for the grid prior.

  • seed (int | Generator | None) – Seed or generator.

Return type:

NDArray[double]

Returns:

An array of shape (n_replications, nobs, k) aligned with observed.

Raises:

SpecificationError – If the count is not positive, the stated degrees of freedom do not admit a covariance, or the prior is unusable.