cov2pcov: Partial Covariance Matrix

In biotools: Tools for Biometry and Applied Statistics in Agricultural Science

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.

Author(s)

Anderson Rodrigo da Silva <anderson.agro at hotmail.com>

See Also

cov

Examples

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

# End (Not run)

biotools documentation built on April 3, 2025, 9:55 p.m.