Generalized partial correlation coefficient between Xi and Xj after removing the effect of all others.

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Description

This function uses a generalized correlation matrix R* as input to compute generalized partial correlations between X_i and X_j where j can be any one of the remaining variables. Computaion removes the effect of all other variables in the matrix. The user is encouraged to remove all known irrelevant rows and columns from the R* matrix before submitting it to this function.

Usage

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parcor_ijk(x, i, j)

Arguments

x

Input a p by p matrix R* of generalized correlation coefficients.

i

A column number identifying the first variable.

j

A column number identifying the second variable.

Value

ouij

Partial correlation Xi with Xj (=cause) after removing all other X's

ouji

Partial correlation Xj with Xi (=cause) after removing all other X's

myk

A list of column numbers whose effect has been removed

Note

This function calls minor, and cofactor and is called by parcor_ridge.

Examples

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## Not run: 
set.seed(34);x=matrix(sample(1:600)[1:99],ncol=3)
colnames(x)=c('V1', 'v2', 'V3')
gm1=gmcmtx0(x)
parcor_ijk(gm1, 2,3)

## End(Not run)#' 

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