u.xenv | R Documentation |
This function outputs dimensions selected by Akaike information criterion (AIC), Bayesian information criterion (BIC) and likelihood ratio testing with specified significance level for the predictor envelope model.
u.xenv(X, Y, alpha = 0.01)
X |
Predictors. An n by p matrix, p is the number of predictors and n is number of observations. The predictors must be continuous variables. |
Y |
Responses. An n by r matrix, r is the number of responses. The response can be univariate or multivariate and must be continuous variable. |
alpha |
Significance level for testing. The default is 0.01. |
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 p. |
aic.seq |
AIC value for dimension from 0 to p. |
bic.seq |
BIC value for dimension from 0 to p. |
data(wheatprotein)
X <- wheatprotein[, 1:6]
Y <- wheatprotein[, 7]
u <- u.xenv(X, Y)
u
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.