u.xenv {Renvlp}

Select the dimension of xenv

Description

This function outputs dimensions selected by Akaike information criterion (AIC), Bayesian information criterion (BIC) and likelihood ratio testing with specified significance level for the predictor envelope model.

Usage

u.xenv(X, Y, alpha = 0.01)

Arguments

X

Predictors. An n by p matrix, p is the number of predictors and n is number of observations. The predictors must be continuous variables.

Y

Responses. An n by r matrix, r is the number of responses. The response can be univariate or multivariate and must be continuous variable.

alpha

Significance level for testing. The default is 0.01.

Value

u.aic

Dimension of the envelope subspace selected by AIC.

u.bic

Dimension of the envelope subspace selected by BIC.

u.lrt

Dimension of the envelope subspace selected by the likelihood ratio testing procedure.

loglik.seq

Log likelihood for dimension from 0 to p.

aic.seq

AIC value for dimension from 0 to p.

bic.seq

BIC value for dimension from 0 to p.

Examples

data(wheatprotein)
X <- wheatprotein[, 1:6]
Y <- wheatprotein[, 7]

u <- u.xenv(X, Y)
u