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Compute bootstrap standard error for the envelope estimator.
boot.env(X, Y, u, B)
Predictors. An n by p matrix, p is the number of predictors. The predictors can be univariate or multivariate, discrete or continuous.
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.
Dimension of the envelope. An integer between 0 and r.
Number of bootstrap samples. A positive integer.
The output is an r by p matrix.
The standard error for elements in beta computed by bootstrap.
This function computes the bootstrap standard errors for the regression coefficients in the envelope model by bootstrapping the residuals.
# NOT RUN { data(wheatprotein) X <- wheatprotein[, 8] Y <- wheatprotein[, 1:6] u <- u.env(X, Y) u B <- 100 bootse <- boot.env(X, Y, 1, B) bootse # }
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