Vinecop.bic
- Vinecop.bic(self: pyvinecopulib.Vinecop, u: numpy.ndarray[numpy.float64[m, n]] = array([], shape=(0, 0), dtype=float64), num_threads: int = 1) 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
Vinecop.loglik()
) and \(p\) is the (effective) number of parameters of the model. The BIC is a consistent model selection criterion for nonparametric models.- Parameters:
u – An \(n \times (d + k)\) or \(n \times 2d\) matrix of evaluation points, where \(k\) is the number of discrete variables (see
Vinecop.select()
orVinecop.pdf()
).num_threads – The number of threads to use for computations; if greater than 1, the function will be applied concurrently to
num_threads
batches ofu
.
- Returns:
The BIC as a double.