h-methods

h,copula-method

h,indepCopula-method

h,normalCopula-method

h,tCopula-method

h,claytonCopula-method

h,gumbelCopula-method

h,fgmCopula-method

h,frankCopula-method

h,galambosCopula-method

copula

To avoid numerical problems for extreme values, the values of
    <code>x</code>, <code>v</code> and return values close to <code>0</code> and <code>1</code> are
    substituted by <code>eps</code> and <code>1 - eps</code>, respectively. The default
    <code>eps</code> value for most of the copulas is <code>.Machine$double.eps^0.5</code>.


The $h$ function represents the conditional distribution function of a
bivariate copula and it should be defined for every copula used in
a pair-copula construction. It is defined as the partial derivative of the
distribution function of the copula w.r.t. the second argument
$h(x,v) = F(x|v) = \partial C(x,v) / \partial v$.


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.

h-methods: Methods for the h-functions

Description

Usage

Arguments

Methods

References