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#' @export
#' @keywords internal
summary.SIR_threshold = function(object, ...) {
if (!inherits(object, "SIR_threshold"))
stop("Only use with \"SIR_threshold\" obects")
cat("\nCall:\n", deparse(object$call), "\n", sep = "")
cat("\n===== Thresholded Sliced Inverse Regression =====", "\n")
cat("\n")
cat(paste("Number of observations:", object$n), "\n")
cat(paste("Number of variables in X:", object$p), "\n")
cat(paste("Number of slices:", object$H), "\n")
cat(paste("Thresholding parameter lambda:", signif(object$lambda, 3)), "\n")
cat(paste("Thresholding method:", object$thresholding))
cat("\n")
cat("\n")
cat(paste("Number of selected variables = ", length(object$list_relevant_variables),
" over the ", object$p, " available variables"), fill = TRUE)
cat(paste("List of relevant variables:", paste(object$list_relevant_variables,
collapse = ",")), "\n")
cat("\n")
cat("Results of EDR directions estimation:\n")
res <- matrix(object$b, ncol = 1)
if (!is.null(colnames(object$b))) {
rownames(res) <- colnames(object$b)
} else {
rownames(res) <- paste("X", 1:object$p, sep = "")
}
colnames(res) <- "Estimated direction"
cat("\n")
prmatrix(signif(res, 3))
cat("\n")
cat("Estimate a new SIR model on the relevant variables with :\n")
varname = deparse(substitute(object))
cat(paste("\t SIR(Y=", varname, "$Y, X=", varname, "$X_reduced, H=", varname, "$H)\n", sep = ""))
}
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