cv.rrr: Reduced-rank regression with rank selected by cross...

In rrpack: Reduced-Rank Regression

Reduced-rank regression with rank selected by cross validation

Description

Reduced-rank regression with rank selected by cross validation

Usage

cv.rrr(
  Y,
  X,
  nfold = 10,
  maxrank = min(dim(Y), dim(X)),
  norder = NULL,
  coefSVD = FALSE
)

Arguments

Y	response matrix
X	covariate matrix
nfold	number of folds
maxrank	maximum rank allowed
norder	for constructing the folds
coefSVD	If TRUE, svd of the coefficient is retuned

Value

a list containing rr estimates from cross validation

References

Chen, K., Dong, H. and Chan, K.-S. (2013) Reduced rank regression via adaptive nuclear norm penalization. Biometrika, 100, 901–920.

Examples

library(rrpack)
p <- 50; q <- 50; n <- 100; nrank <- 3
mydata <- rrr.sim1(n, p, q, nrank, s2n = 1, sigma = NULL,
                   rho_X = 0.5, rho_E = 0.3)
rfit_cv <- with(mydata, cv.rrr(Y, X, nfold = 10, maxrank = 10))
summary(rfit_cv)
coef(rfit_cv)

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