Compute bootstrap standard error for the scaled predictor envelope estimator.
Usage
boot.sxenv(X, Y, u, R, B)
Value
The output is an p by r matrix.
bootse
The standard error for elements in beta computed by bootstrap.
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.
data(sales)
Y <- sales[, 1:3]
X <- sales[, 4:7]
R <- rep(1, 4)
u <- u.sxenv(X, Y, R)
u
B <- 100
if (FALSE) bootse <- boot.sxenv(X, Y, 2, R, B)
if (FALSE) bootse