u.stenv: Select the dimension of stenv

In Renvlp: Computing Envelope Estimators

Select the dimension of stenv

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 simultaneous envelope model.

Usage

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

Arguments

X	Predictors. An n by p matrix, p is the number of predictors. The predictors can be univariate or multivariate, discrete or continuous.
Y	Multivariate responses. An n by r matrix, r is the number of responses and n is number of observations. The responses must be continuous variables.
alpha	Significance level for testing. The default is 0.01.

Value

d	Rank of beta selected by the Bura-Cook estimator.
u.aic	Dimension of the simultaneous envelope subspace selected by AIC.
u.bic	Dimension of the simultaneous envelope subspace selected by BIC.
u.lrt	Dimension of the simultaneous envelope subspace selected by the likelihood ratio testing procedure.
loglik.mat	Log likelihood for dimension from (1, 1) to (p, r).
aic.mat	AIC value for dimension from (1, 1) to (p, r).
bic.mat	BIC value for dimension from (1, 1) to (p, r).

Examples

data(fiberpaper)
X <- fiberpaper[, 5:7]
Y <- fiberpaper[, 1:4]

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

Renvlp documentation built on Oct. 11, 2023, 1:06 a.m.