u.env.tcond {Renvlp}

Select the dimension of env.tcond

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 response envelope model with t-distributed errors.

Usage

u.env.tcond(X, Y, df, 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.

df

Degrees of freedom of the t-distribution. A positive number that is greater than 2.

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 r.

aic.seq

AIC value for dimension from 0 to r.

bic.seq

BIC value for dimension from 0 to r.

Examples

data(concrete)
X <- concrete[1:78, 1:7]  # The first 78 observations are training data
Y <- concrete[1:78, 8:10]
## Not run: u <- u.env.tcond(X, Y, 6)
## Not run: u