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
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.- Parameter
u
: An \(n \times (2 + k)\) matrix of observations contained in \((0, 1)\), where \(k\) is the number of discrete variables.
- Parameter
psi0
: Prior probability of a non-independence copula.
- Parameter