boot.sxenv | R Documentation |
Compute bootstrap standard error for the scaled predictor envelope estimator.
boot.sxenv(X, Y, u, R, B)
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. |
This function computes the bootstrap standard errors for the regression coefficients in the scaled envelope model in the predictor space by bootstrapping the residuals.
The output is an p by r matrix.
bootse |
The standard error for elements in beta computed by bootstrap. |
data(sales)
Y <- sales[, 1:3]
X <- sales[, 4:7]
R <- rep(1, 4)
u <- u.sxenv(X, Y, R)
u
B <- 100
## Not run: bootse <- boot.sxenv(X, Y, 2, R, B)
## Not run: bootse
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