polar: The left polar decomposition.

In dcgerard/tensr: Covariance Inference and Decompositions for Tensor Datasets

The left polar decomposition.

Description

polar calculates the left polar decomposition of a matrix.

Usage

polar(X)

Arguments

X

A matrix.

Details

polar Takes a matrix X, of dimensions n by p, and returns two matrices P and Z such that X = PZ. P is a symmetric positive definite matrix of dimension n by n and Z is an n by p matrix with orthonormal rows.

Value

P A n by n symmetric positive definite matrix.

Z A n by p matrix with orthonormal rows.

Note that X == P %*% Z, up to numerical precision.

Author(s)

David Gerard.

Examples

X <- matrix(1:6, nrow = 2)
polar_x <- polar(X)
P <- polar_x$P
Z <- polar_x$Z
P
Z
trim(Z %*% t(Z))
trim(X - P %*% Z)

dcgerard/tensr documentation built on Oct. 4, 2022, 5:58 p.m.