vineFitML-class

show,vineFitML-method


Extends the <code>vineFit</code> class to include information
about the Maximum Likelihood inference.


multivariate

classes

models

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.

Yasser GonzalezFernandez

vines

Multivariate Dependence Modeling with Vines

vineFitML-class function

See <code>vineFit</code> for information about inherited slots. <dl> </dl> 

Slots

Methods

Class for the Results of Vine Inference by Maximum Likelihood

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

Description

Arguments

Slots

Methods

See Also