RQ: RQ Factorization of a matrix

In LSE: Constrained Least Squares and Generalized QR Factorization

Description

RQ factorization allows to develop an orthogonal transformation in a matrix through Householder reflections. Requires pracma package.

Usage

RQ(y)

Arguments

y	Numeric matrix or vector.

Details

RQ factorization make a orthogonal transformation at the rows of the matrix, beginning in the last one, and finishing with the first one row.

Value

Q	Orthogonal matrix for x
R	Triangular matrix for x

Author(s)

Sergio Andrés Cabrera Miranda Statician [e-mail]

Examples

A = matrix(runif(12,0,5),4,3,byrow=TRUE)
RQ(A)

LSE documentation built on Feb. 2, 2022, 5:07 p.m.