This function outputs dimensions selected by Akaike information criterion (AIC), Bayesian information criterion (BIC) and likelihood ratio testing with specified significance level for the heteroscedastic envelope model.
u.henv(X, Y, alpha = 0.01)
Dimension of the heteroscedastic envelope subspace selected by AIC.
Dimension of the heteroscedastic envelope subspace selected by BIC.
Dimension of the heteroscedastic envelope subspace selected by the likelihood ratio testing procedure.
Log likelihood for dimension from 0 to r.
AIC value for dimension from 0 to r.
BIC value for dimension from 0 to r.
A group indicator vector of length
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.
Significance level for testing. The default is 0.01.
data(waterstrider)
X <- waterstrider[ , 1]
Y <- waterstrider[ , 2:5]
if (FALSE) u <- u.henv(X, Y)
if (FALSE) u
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