Bicop.mbic

Bicop.mbic(self: pyvinecopulib.Bicop, u: numpy.ndarray[numpy.float64[m, n]] = array([], shape=(0, 2), dtype=float64), psi0: float = 0.9) → float

Evaluates the modified Bayesian information criterion (mBIC).

The mBIC is defined as

\[\mathrm{BIC} = -2\, \mathrm{loglik} + p \log(n) - 2 (I \log(\psi_0) + (1 - I) \log(1 -\]

psi_0),

where \(\mathrm{loglik}\) is the log-liklihood (see Bicop.loglik()), \(p\) is the (effective) number of parameters of the model, and \(\psi_0\) is the prior probability of having a non-independence copula and \(I\) is an indicator for the family being non-independence.

Parameters:

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

• psi0 – Prior probability of a non-independence copula.

Returns:

The mBIC evaluated at u.