boot.sxenv: Bootstrap for sxenv

In Renvlp: Computing Envelope Estimators

Bootstrap for sxenv

Description

Compute bootstrap standard error for the scaled predictor envelope estimator.

Usage

boot.sxenv(X, Y, u, R, 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 in the predictor space. An integer between 0 and p.
R	The number of replications of the scales. A vector, the sum of all elements of R must be p.
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 in the predictor space by bootstrapping the residuals.

Value

The output is an p by r matrix.

bootse

The standard error for elements in beta computed by bootstrap.

Examples

data(sales)
Y <- sales[, 1:3]
X <- sales[, 4:7]
R <- rep(1, 4)

u <- u.sxenv(X, Y, R)
u

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

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