Renvlp (version 3.4.5)

u.rrenv.apweights: Select the dimension of rrenv.apweights

Description

This function outputs the envelope dimension selected by Akaike information criterion (AIC), Bayesian information criterion (BIC) and likelihood ratio testing with specified significance level for the reduced rank envelope model with nonconstant error variance.

Usage

u.rrenv.apweights(X, Y, d, alpha = 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 d to r.

aic.seq

AIC value for dimension from d to r.

bic.seq

BIC value for dimension from d to r.

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.

d

The rank of the coefficient matrix. An integer between 0 and r.

alpha

Significance level for testing. The default is 0.01.

Examples

data(vehicles)
X <- vehicles[, 1:11]  
Y <- vehicles[, 12:15]
X <- scale(X)
Y <- scale(Y)  # The scales of Y are vastly different, so scaling is reasonable here
d <- d.select(X, Y, 0.01)
d

if (FALSE) u <- u.rrenv.apweights(X, Y, 2)
if (FALSE) u