Multivariate Dependence Modeling with Vines
Class for the Results of Vine Goodness-of-fit Tests
Vine Goodness-of-fit Tests
Vine Log-likelihood Evaluation
Methods for the h-functions
Methods for the Inverse of the h-functions
Classes for Regular Vines
Base Vine Class
Vine Distribution Functions
Create Vine Objects
Class for the Results of Vine Inference
Vine Inference
Class for the Results of Vine Inference by Maximum Likelihood
Select an Order of the Variables
Parameters of a Vine
Vine Probability Integral Transform Methods
Implementation of the vine graphical model for building high-dimensional probability distributions as a factorization of bivariate copulas and marginal density functions. This package provides S4 classes for vines (C-vines and D-vines) and methods for inference, goodness-of-fit tests, density/distribution function evaluation, and simulation.