Learn R Programming

Renvlp (version 2.7)

boot.env: Bootstrap for env

Description

Compute bootstrap standard error for the envelope estimator.

Usage

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

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.

u

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

B

Number of bootstrap samples. A positive integer.

Value

The output is an r by p matrix.

bootse

The standard error for elements in beta computed by bootstrap.

Details

This function computes the bootstrap standard errors for the regression coefficients in the envelope model by bootstrapping the residuals.

Examples

Run this code
# NOT RUN {
data(wheatprotein)
X <- wheatprotein[, 8]
Y <- wheatprotein[, 1:6]

u <- u.env(X, Y)
u

B <- 100
bootse <- boot.env(X, Y, 1, B)
bootse
# }

Run the code above in your browser using DataLab