Renvlp (version 2.7)

boot.senv: Bootstrap for senv

Description

Compute bootstrap standard error for the scaled 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.

Value

The output is an r by p matrix.

bootse

The standard error for elements in beta computed by bootstrap.

Details

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

Examples

# NOT RUN {
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
# }