Bicop.bic

Bicop.bic(self, u: numpy.ndarray = 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 loglik()) and \(p\)is the (effective) number of parameters of the model. The BIC is a consistent model selection criterion for parametric models.

Parameters:

undarray, shape (n, m), dtype float

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

Returns:

float

The BIC evaluated at u.