Bicop.bic

Bicop.bic(self: pyvinecopulib.Bicop, u: numpy.ndarray[numpy.float64[m, n]] = array([], shape=(0, 2), dtype=float64)) → float

Evaluates the Bayesian information criterion (BIC).

The BIC is defined as

\[\mathrm{BIC} = -2\, \mathrm{loglik} + \log(n) p,\]

where \(\mathrm{loglik}\) is the log-liklihood (see Bicop.loglik()) and \(p\) is the (effective) number of parameters of the model. The BIC is a consistent model selection criterion for parametric models.

Parameters:

u – An \(n \times (2 + k)\) matrix of observations contained in \((0, 1)\), where \(k\) is the number of discrete variables.

Returns:

The BIC evaluated at u.