Description Usage Arguments Value Examples
View source: R/partial_correlation.R
Estimates the inverse covariance matrix then uses this matrix to calculate partial correlation coefficents.
Assumes that matrix rows correspond to different variables of interest.
The one exception is if method="correlation"
; see below for details.
1  partial_correlation(mat, method, verbose=FALSE)

mat 
Input matrix. 
method 
One of the following

verbose 
Binary flag determining whether diagnostic output is shown. 
Returns a m x m upper triangular matrix of partial correlation coefficients from an input m x n matrix.
1 2 3 4 5 6 7 8  # load highly collinear economic data time series
data(longley)
longley_ss < t(longley[,c(1:5,7)]) # put data in correct input format
colors < colorRampPalette(c("red","white","blue"))(10)
pc_shrinkage < partial_correlation(longley_ss,method="shrinkage")
image(pc_shrinkage,zlim=c(1,1),col=colors)

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