boot.rrenv.apweights {Renvlp}

Bootstrap for rrenv.apweights

Description

Compute bootstrap standard error for the reduced rank envelope estimator with nonconstant error covariance.

Usage

boot.rrenv.apweights(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 that accommodates nonconstant error covariance.

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 <- 10
## Not run: bootse <- boot.rrenv.apweights(X, Y, 3, 2, B)
## Not run: bootse