Bicop
- class Bicop
A class for bivariate copula models.
The model is fully characterized by the family, rotation (one of
0
,90
,180
,270
), a matrix of parameters, and variable types (two strings, one for each variable, either"c"
for continuous or"d"
for discrete).Implemented families (see
BicopFamily
):| type | full name | string identifier | |---------------|-----------------------|-----------------------| | - | Independence | "indep" | | Elliptical | Gaussian | "gaussian" | | | Student t | "student" | | Archimedean | Clayton | "clayton" | | | Gumbel | "gumbel" | | | Frank | "frank" | | | Joe | "joe" | | | Clayton-Gumbel (BB1) | "bb1" | | | Joe-Gumbel (BB6) | "bb6" | | | Joe-Clayton (BB7) | "bb7" | | | Joe-Frank (BB8) | "bb8" | | Extreme-Value | Tawn | "tawn" | | Nonparametric | Transformation kernel | "tll" |
Attributes
family
The copula family.
nobs
The number of observations (only for fitted objects).
npars
The number of parameters (for nonparametric families, a conceptually similar definition).
parameters
The copula parameter(s).
rotation
The copula rotation.
tau
The Kendall's tau.
var_types
The type of the two variables.
Methods
Creates a new instance of the class.
Evaluates the Akaike information criterion (AIC).
Evaluates the Bayesian information criterion (BIC).
Evaluates the copula distribution.
Fits a bivariate copula (with fixed family) to data.
Evaluates the first h-function.
Evaluates the second h-function.
Evaluates the inverse of the first h-function.
Evaluates the inverse of the second h-function.
Evaluates the log-likelihood.
Evaluates the modified Bayesian information criterion (mBIC).
Gets lower bounds for copula parameters.
Converts the copula parameters to Kendall's \(tau\).
Gets upper bounds for copula parameters.
Evaluates the copula density.
Generates a plot for the Bicop object.
Selects the best fitting model.
Simulates from a bivariate copula.
Summarizes the model into a string (can be used for printing).
Converts a Kendall's \(\tau\) into copula parameters for one-parameter families.
Write the copula object into a JSON file.