Vinecop

class Vinecop(*args, **kwargs)

A class for vine copula models.

A vine copula model is characterized by its structure (see RVineStructure objects) and the pair-copulas (see Bicop objects).

Attributes

`dim`	The dimension.
`families`	Families of all pair-copulas.
`matrix`	Extracts the R-vine structure's matrix.
`nobs`	The number of observations (for fitted objects only).
`npars`	The total number of parameters.
`order`	The R-vine structure's order.
`pair_copulas`	All pair-copulas.
`parameters`	The parameters of all pair-copulas.
`rotations`	The rotations of all pair-copulas.
`structure`	The R-vine structure.
`taus`	The Kendall's taus of all pair-copulas.
`threshold`	The threshold (for thresholded copulas only).
`trunc_lvl`	The truncation level.
`var_types`	The types of each variables.

Methods

`__init__`	Default constructor for the `Vinecop` class.
`aic`	Evaluates the Akaike information criterion (AIC).
`bic`	Evaluates the Bayesian information criterion (BIC).
`cdf`	Evaluates the copula distribution.
`fit`	Fits the parameters of a pre-specified vine copula model.
`format`	Summarizes the model into a string (can be used for printing).
`from_data`	Factory function to create a Vinecop from data.
`from_dimension`	Instantiates a D-vine with all pair-copulas set to independence.
`from_file`	Instantiates from a JSON file.
`from_json`	Instantiates from a nlohmann::json object.
`from_structure`	Factory function to create a Vinecop using either a structure or a matrix.
`get_family`	Gets the family of a pair-copula.
`get_pair_copula`	Gets a pair-copula.
`get_parameters`	Gets the parameters of a pair-copula.
`get_rotation`	Gets the rotation of a pair-copula.
`get_tau`	Gets the kendall's tau of a pair-copula.
`inverse_rosenblatt`	Evaluates the inverse Rosenblatt transform.
`loglik`	Evaluates the log-likelihood.
`mbicv`	Evaluates the modified Bayesian information criterion for vines (mBICV).
`pdf`	Evaluates the copula density.
`plot`	Generates a plot for the Vinecop object.
`rosenblatt`	Evaluates the Rosenblatt transform for a vine copula model.
`select`	In other words, `select()` behaves differently depending on its current truncation level and the truncation level specified in the controls, respectively called `trunc_lvl` and `.` in what follows.
`simulate`	Simulates from a vine copula model, see `inverse_rosenblatt()`.
`to_file`	Writes the copula object into a JSON file.
`to_json`	Converts the copula into a nlohmann::json object.
`truncate`	Truncates the vine copula model.