FitControlsBicop.__init__

FitControlsBicop.__init__(self: pyvinecopulib.FitControlsBicop, family_set: List[pyvinecopulib.BicopFamily] = [<BicopFamily.indep: 0>, <BicopFamily.gaussian: 1>, <BicopFamily.student: 2>, <BicopFamily.clayton: 3>, <BicopFamily.gumbel: 4>, <BicopFamily.frank: 5>, <BicopFamily.joe: 6>, <BicopFamily.bb1: 7>, <BicopFamily.bb6: 8>, <BicopFamily.bb7: 9>, <BicopFamily.bb8: 10>, <BicopFamily.tll: 11>], parametric_method: str = 'mle', nonparametric_method: str = 'quadratic', nonparametric_mult: float = 1.0, selection_criterion: str = 'bic', weights: numpy.ndarray[numpy.float64[m, 1]] = array([], dtype=float64), psi0: float = 0.9, preselect_families: bool = True, num_threads: int = 1) → None

Instantiates the controls for fitting bivariate copula models.

Parameter family_set:

The set of copula families to consider (if empty, then all families are included).

Parameter parametric_method:

The fit method for parametric families; possible choices: "mle", "itau".

Parameter nonparametric_method:

The fit method for the local-likelihood nonparametric family (TLLs); possible choices: "constant", "linear", "quadratic".

Parameter nonparametric_mult:

A factor with which the smoothing parameters are multiplied.

Parameter selection_criterion:

The selection criterion ("loglik", "aic" or "bic").

Parameter weights:

A vector of weights for the observations.

Parameter psi0:

Only for `selection_criterion = “mbic”, the prior probability of non-independence.

Parameter preselect_families:

Whether to exclude families before fitting based on symmetry properties of the data.

Parameter num_threads:

Number of concurrent threads to use while fitting copulas for different families; never uses more than the number of concurrent threads supported by the implementation.