boot.env: Bootstrap for env

In therimalaya/envelope: Computing Envelope Estimators in Multivariate Linear Regression

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.

Details

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

Value

The output is an r by p matrix.

bootse

The standard error for elements in beta computed by bootstrap.

Examples

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

therimalaya/envelope documentation built on May 29, 2019, 1:38 p.m.