Compute bootstrap standard error for the envelope estimator.
Usage
boot.xenv(X, Y, u, B)
Arguments
X
Predictors. An n by p matrix, p is the number of predictors and n is number of observations. The predictors must be continuous variables.
Y
Responses. An n by r matrix, r is the number of responses. The response can be univariate or multivariate and must be continuous variable.
u
Dimension of the envelope. An integer between 0 and p.
B
Number of bootstrap samples. A positive integer.
Value
The output is a p by r 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 envelope model in predictor space by bootstrapping the residuals.
# NOT RUN {data(wheatprotein)
X <- wheatprotein[, 1:6]
Y <- wheatprotein[, 7]
# }# NOT RUN {B <- 100
# }# NOT RUN {bootse <- boot.xenv(X, Y, 2, B)
# }# NOT RUN {bootse
# }