Renvlp (version 2.7)

boot.logit.env: Bootstrap for logit.env

Description

Compute bootstrap standard error for the envelope estimator in logistic regression.

Usage

boot.logit.env(X, Y, u, B)

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.

u

Dimension of the envelope. An integer between 0 and p.

B

Number of bootstrap samples. A positive integer.

Value

The output is a p by 1 matrix.

bootse

The standard error for elements in beta computed by bootstrap.

Details

This function computes the bootstrap standard errors for the coefficients in the logistic regression envelope by the paired bootstrap.

Examples

# NOT RUN {
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))

B <- 100
# }
# NOT RUN {
bootse <- boot.logit.env(X, Y, 1, B)
# }
# NOT RUN {
bootse
# }