rrr.fit: Fitting reduced-rank regression with a specific rank

In rrpack: Reduced-Rank Regression

Fitting reduced-rank regression with a specific rank

Description

Given a response matrix and a covariate matrix, this function fits reduced rank regression for a specified rank. It reduces to singular value decomposition if the covariate matrix is the identity matrix.

Usage

rrr.fit(Y, X, nrank = 1, weight = NULL, coefSVD = FALSE)

Arguments

Y	a matrix of response (n by q)
X	a matrix of covariate (n by p)
nrank	an integer specifying the desired rank
weight	a square matrix of weight (q by q); The default is the identity matrix
coefSVD	logical indicating the need for SVD for the coeffient matrix in the output; used in ssvd estimation

Value

S3 rrr object, a list consisting of

coef	coefficient of rrr
coef.ls	coefficient of least square
fitted	fitted value of rrr
fitted.ls	fitted value of least square
A	right singular matrix
Ad	a vector of sigular values
rank	rank of the fitted rrr

Examples

Y <- matrix(rnorm(400), 100, 4)
X <- matrix(rnorm(800), 100, 8)
rfit <- rrr.fit(Y, X, nrank = 2)
coef(rfit)

rrpack documentation built on June 16, 2022, 9:05 a.m.