boot.rrenv: Bootstrap for rrenv

In Renvlp: Computing Envelope Estimators

Bootstrap for rrenv

Description

Compute bootstrap standard error for the reduced rank envelope estimator.

Usage

boot.rrenv(X, Y, u, d, 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.
d	The rank of the coefficient matrix. An integer between 0 and u.
B	Number of bootstrap samples. A positive integer.

Details

This function computes the bootstrap standard errors for the regression coefficients in the reduced rank envelope model.

Value

The output is an r by p matrix.

bootse

The standard error for elements in beta computed by bootstrap.

Examples

data(vehicles)
X <- vehicles[, 1:11]  
Y <- vehicles[, 12:15]
X <- scale(X)
Y <- scale(Y)  # The scales of Y are vastly different, so scaling is reasonable here

B <- 100
## Not run: bootse <- boot.rrenv(X, Y, 4, 2, B)
## Not run: bootse

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