biotools (version 2.2)

cov2pcov: Partial Covariance Matrix

Description

Compute a matrix of partial (co)variances for a group of variables with respect to another. Take $\Sigma$ as the covariance matrix of dimension p. Now consider dividing $\Sigma$ into two groups of variables. The partial covariance matrices are calculate by: $$\Sigma_{11.2} = \Sigma_{11} - \Sigma_{12} \Sigma_{22}^{-1} \Sigma_{21}$$ $$\Sigma_{22.1} = \Sigma_{22} - \Sigma_{21} \Sigma_{11}^{-1} \Sigma_{12}$$

Usage

cov2pcov(m, vars1, vars2 = seq(1, ncol(m))[-vars1])

Arguments

m

a square numeric matrix.

vars1

a numeric vector indicating the position (rows or columns in m) of the set of variables at which to compute the partial covariance matrix.

vars2

a numeric vector indicating the position (rows or columns in m) of the set of variables at which to adjust the partial covariance matrix.

Value

• A square numeric matrix.

See Also

cov

Examples

(Cl <- cov(longley))
cov2pcov(Cl, 1:2)

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