Learn R Programming

vines (version 1.1.5)

Multivariate Dependence Modeling with Vines

Description

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.

Copy Link

Version

Install

install.packages('vines')

Monthly Downloads

117

Version

1.1.5

License

GPL (>= 2)

Issues

Pull Requests

Stars

Forks

Maintainer

Yasser GonzalezFernandez

Last Published

July 28th, 2016

Functions in vines (1.1.5)

Vine

Create Vine Objects
RVine-classes

Classes for Regular Vines
Vine-class

Base Vine Class
h-methods

Methods for the h-functions
vineFitML-class

Class for the Results of Vine Inference by Maximum Likelihood
vineGoF-class

Class for the Results of Vine Goodness-of-fit Tests
vineFit

Vine Inference
Vine-distribution

Vine Distribution Functions
hinverse-methods

Methods for the Inverse of the h-functions
vineFit-class

Class for the Results of Vine Inference
vineGoF

Vine Goodness-of-fit Tests
vineLogLik

Vine Log-likelihood Evaluation
vineOrder

Select an Order of the Variables
vineParameters

Parameters of a Vine
vinePIT-methods

Vine Probability Integral Transform Methods