cv.mrrr: Mixed-response reduced-rank regression with rank selected by...

In rrpack: Reduced-Rank Regression

Mixed-response reduced-rank regression with rank selected by cross validation

Description

Mixed-response reduced-rank regression with rank selected by cross validation

Usage

cv.mrrr(
  Y,
  X,
  is.pca = NULL,
  offset = NULL,
  ctrl.id = c(),
  family = list(gaussian(), binomial(), poisson()),
  familygroup = NULL,
  maxrank = min(ncol(Y), ncol(X)),
  penstr = list(),
  init = list(),
  control = list(),
  nfold = 5,
  foldid = NULL,
  nlam = 20,
  warm = FALSE
)

Arguments

Y	response matrix
X	covariate matrix
is.pca	If TRUE, mixed principal component analysis with X=I
offset	matrix of the same dimension as Y for offset
ctrl.id	indices of unpenalized predictors
family	a list of family functions as used in glm
familygroup	a list of family indices of the responses
maxrank	integer giving the maximum rank allowed.
penstr	a list of penalty structure of SVD.
init	a list of initial values of kappaC0, kappaS0, C0, and S0
control	a list of controling parameters for the fitting
nfold	number of folds in cross validation
foldid	to specify the folds if desired
nlam	number of tuning parameters; not effective when using rank constrained estimation
warm	if TRUE, use warm start in fitting the solution paths

Value

S3 mrrr object, a list containing

fit	the output from the selected model
dev	deviance measures

Examples

## Not run: 
library(rrpack)
simdata <- rrr.sim3(n = 100, p = 30, q.mix = c(5, 20, 5),
                    nrank = 2, mis.prop = 0.2)
Y <- simdata$Y
Y_mis <- simdata$Y.mis
X <- simdata$X
X0 <- cbind(1,X)
C <- simdata$C
family <- simdata$family
familygroup <- simdata$familygroup
svdX0d1 <- svd(X0)$d[1]
init1 = list(kappaC0 = svdX0d1 * 5)
offset = NULL
control = list(epsilon = 1e-4, sv.tol = 1e-2, maxit = 2000,
               trace = FALSE, gammaC0 = 1.1, plot.cv = TRUE,
               conv.obj = TRUE)
fit.cv.mrrr <- cv.mrrr(Y_mis, X, family = family,
                       familygroup = familygroup,
                       maxrank = 20,
                       penstr = list(penaltySVD = "rankCon",
                                     lambdaSVD = c(1 : 6)),
                       control = control, init = init1,
                       nfold = 10, nlam = 50)
summary(fit.cv.mrrr)
coef(fit.cv.mrrr)
fit.mrrr <- fit.cv.mrrr$fit

## plot(svd(fit.mrrr$coef[- 1,])$d)
plot(C ~ fit.mrrr$coef[- 1, ])
abline(a = 0, b = 1)

## End(Not run)

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