u.logit.env: Select the dimension of logit.env

In Renvlp: Computing Envelope Estimators

Select the dimension of logit.env

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 envelope model in logistic regression.

Usage

u.logit.env(X, Y, alpha = 0.01)

Arguments

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	Response. An n by 1 matrix. The univariate response must be binary.
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 p.
aic.seq	AIC value for dimension from 0 to p.
bic.seq	BIC value for dimension from 0 to p.

Examples

data(horseshoecrab)
X1 <- as.numeric(horseshoecrab[ , 1] == 2)
X2 <- as.numeric(horseshoecrab[ , 1] == 3)
X3 <- as.numeric(horseshoecrab[ , 1] == 4)
X4 <- as.numeric(horseshoecrab[ , 2] == 2)
X5 <- as.numeric(horseshoecrab[ , 2] == 3)
X6 <- horseshoecrab[ , 3]
X7 <- horseshoecrab[ , 5]
X <- cbind(X1, X2, X3, X4, X5, X6, X7)
Y <- as.numeric(ifelse(horseshoecrab[ , 4] > 0, 1, 0))

## Not run: u <- u.logit.env(X, Y)
## Not run: u

Renvlp documentation built on Oct. 11, 2023, 1:06 a.m.