boot.senv: Bootstrap for senv

In Renvlp: Computing Envelope Estimators

Bootstrap for senv

Description

Compute bootstrap standard error for the scaled response envelope estimator.

Usage

boot.senv(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 scaled 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 scaled 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(sales)
X <- sales[, 1:3]
Y <- sales[, 4:7]

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

## Not run: B <- 100
## Not run: bootse <- boot.senv(X, Y, 2, B)
## Not run: bootse

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