This function outputs dimensions selected by Akaike information criterion (AIC), Bayesian information criterion (BIC) and likelihood ratio testing with specified significance level for the groupwise envelope model.
Usage
u.genv(X, Y, Z, 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.
Z
A group indicator vector of length \(n\), where \(n\)
denotes the number of observations.
alpha
Significance level for testing. The default is 0.01.
Value
u.aic
Dimension of the groupwise envelope subspace selected by AIC.
u.bic
Dimension of the groupwise envelope subspace selected by BIC.
u.lrt
Dimension of the groupwise envelope subspace selected by the likelihood ratio testing procedure.
# NOT RUN {data(fiberpaper)
X <- fiberpaper[ , c(5, 7)]
Y <- fiberpaper[ , 1:3]
Z <- as.numeric(fiberpaper[ , 6] > mean(fiberpaper[ , 6]))
u <- u.genv(X, Y, Z)
u
# }