RVineCor2pcor: (Partial) Correlations for R-Vine Copula Models

In VineCopula: Statistical Inference of Vine Copulas

(Partial) Correlations for R-Vine Copula Models

Description

Correlations to partial correlations and vice versa for R-vines with independence, Gaussian and t-copulas.

Usage

RVineCor2pcor(RVM, corMat)

RVinePcor2cor(RVM)

Arguments

RVM	RVineMatrix() defining only the R-vine structure for Cor2pcor and providing as well the partial correlations for Pcor2cor.
corMat	correlation matrix

Value

RVM	RVineMatrix with transformed partial correlations (for Cor2pcor)
cor	correlation matrix (for Pcor2cor)

Note

The behavior of RVinePcor2ccor differs from older versions (<= 1.4). The RVM object is now normalized such that the order of the returned correlation matrix conforms with the correlation matrix of the data. If RVM$names are non-default, the initial ordering of the variables cannot be traced back and the matrix has to be interpreted as indicated by the row- and column names.

Examples

## create RVineMatrix-object for Gaussian vine
Matrix <- matrix(c(1, 3, 4, 2,
                   0, 3, 4, 2,
                   0, 0, 4, 2,
                   0, 0, 0, 2), 4, 4)
family <- matrix(c(0, 1, 1, 1,
                   0, 0, 1, 1,
                   0, 0, 0, 1,
                   0, 0, 0, 0), 4, 4)
par <- matrix(c(0, 0.2,   0, 0.6,
                0,   0, 0.2, 0.6,
                0,   0,   0, 0.6,
                0,   0,   0,   0), 4, 4)
RVM <- RVineMatrix(Matrix, family, par)

## calculate correlation matrix corresponding to the R-Vine model
newcor <- RVinePcor2cor(RVM)

## transform back to partial correlations
RVineCor2pcor(RVM, newcor)$par

## check if they are equal
all.equal(RVM$par, RVineCor2pcor(RVM, newcor)$par)

VineCopula documentation built on July 26, 2023, 5:23 p.m.