pcor: Compute partial correlation matrix or standardized precision...

In rags2ridges: Ridge Estimation of Precision Matrices from High-Dimensional Data

Compute partial correlation matrix or standardized precision matrix

Description

Function computing the partial correlation matrix or standardized precision matrix from an input precision matrix.

Usage

pcor(P, pc = TRUE)

Arguments

P	(Possibly regularized) precision matrix.
pc	A logical indicating if the partial correlation matrix should be computed.

Details

The function assumes that the input matrix is a precision matrix. If pc = FALSE the standardized precision matrix, rather than the partial correlation matrix, is given as the output value. The standardized precision matrix is equal to the partial correlation matrix up to the sign of off-diagonal entries.

Value

A partial correlation matrix or a standardized precision matrix.

Author(s)

Carel F.W. Peeters <[e-mail]>, Wessel N. van Wieringen

See Also

ridgeP, covML

Examples

## Obtain some (high-dimensional) data
p = 25
n = 10
set.seed(333)
X = matrix(rnorm(n*p), nrow = n, ncol = p)
colnames(X)[1:25] = letters[1:25]
Cx <- covML(X)

## Obtain regularized precision matrix
P <- ridgeP(Cx, lambda = 10, type = "Alt")

## Obtain partial correlation matrix
pcor(P)

rags2ridges documentation built on Oct. 14, 2023, 5:06 p.m.