HierarchicalBVARResult.posterior_df

HierarchicalBVARResult.posterior_df: float

Inverse-Wishart posterior degrees of freedom \(\bar\nu\).

k + 2 + nobs + n_dummy: the prior’s k + 2, the smallest value at which the prior covariance mean exists, plus one for every row updated on, sample and dummy rows alike. sigma_u is the posterior scale divided by posterior_df - k - 1.