print.summary.restriktor <- function(x, digits = max(3, getOption("digits") - 2),
signif.stars = getOption("show.signif.stars"), ...) {
resid <- x$residuals
rdf <- x$rdf
se.type <- x$se.type[1]
bootCIs <- attr(x$se.type, "bootCIs")
bty <- attr(x$se.type, "bty")
level <- attr(x$se.type, "level")
cat("\nCall:\n", gsub("\\n", "\n", paste(deparse(x$call), collapse="\n"),
fixed = TRUE), "\n\n", sep = "")
if (inherits(x, "summary.conRLM")) {
cat("Restriktor: restricted robust linear model:\n\n")
} else if (inherits(x, "summary.conGLM")) {
cat("Restriktor: restricted generalized linear model:\n\n")
} else if (inherits(x, "summary.conLM")) {
cat("Restriktor: restricted linear model:\n\n")
} else if (inherits(x, "summary.conMLM")) {
cat("Restriktor: restricted multivariate linear model:\n\n")
}
cat(if (!is.null(x$weights) && diff(range(x$weights)))
"Weighted ", "Residuals:\n", sep = "")
if (rdf > 5L) {
nam <- c("Min", "1Q", "Median", "3Q", "Max")
rq <- if (length(dim(c(resid))) == 2L) {
structure(apply(t(resid), 1L, quantile), dimnames = list(nam,
dimnames(resid)[[2L]]))
} else {
zz <- zapsmall(quantile(resid), digits + 1L)
structure(zz, names = nam)
}
print(rq, digits = digits, ...)
} else if (rdf > 0L) {
print(resid, digits = digits, ...)
}
coefs <- x$coefficients
if (se.type %in% c("boot.model.based", "boot.standard") && bootCIs) {
cat("\nCoefficients from restricted model\nwith",
100 * level, "pct bootstrap confidence intervals (",bty,"):\n ")
} else {
cat("\nCoefficients:\n")
}
printCoefmat(coefs, digits = digits, signif.stars = signif.stars,
na.print = "NA")
if (inherits(x, c("summary.conLM", "summary.conRLM"))) {
if (inherits(x, "summary.conLM")) {
stddev <- sqrt(x$s2)
} else {
stddev <- x$stddev
}
cat("\nResidual standard error:", format(signif(stddev,
digits)), "on", rdf, "degrees of freedom")
}
if (se.type == "standard") {
cat("\nStandard errors:", se.type ,"\n")
} else if (se.type == "const") {
cat("\nHomoskedastic standard errors.\n")
} else if (se.type %in% c("boot.model.based", "boot.standard")) {
if (se.type == "boot.model.based") {
se.type <- "model-based"
} else if (se.type == "boot.standard") {
se.type <- "standard"
}
cat("\nBootstrapped standard errors:", se.type ,"\n")
} else {
cat("\nHeteroskedastic robust standard errors:", se.type ,"\n")
}
if (!(inherits(x, c("summary.conGLM", "summary.conMLM"))) && !is.na(x$R2.reduced)) {
if (all((x$R2.org - x$R2.reduced) < 1e-08)) {
cat("Multiple R-squared remains", sprintf("%5.3f", x$R2.org),"\n")
} else {
cat("Multiple R-squared reduced from", sprintf("%5.3f", x$R2.org), "to",
sprintf("%5.3f", x$R2.reduced),"\n")
}
}
if (inherits(x, "summary.conGLM")) {
cat("\n(Dispersion parameter for ", x$family$family, " family taken to be ",
format(x$dispersion), ")\n\n", apply(cbind(paste(format(c("Null",
"Residual"), justify = "right"), "deviance:"), format(unlist(x[c("deviance.null",
"deviance")]), digits = max(5L, digits + 1L)), " on",
format(unlist(x[c("df.residual.null", "rdf")])), " degrees of freedom\n"),
1L, paste, collapse = " "), sep = "")
}
if (inherits(x, "summary.conRLM")) {
cat("\n")
robWeights(x$wgt)
cat("\n")
}
goric <- x$goric
if (!is.null(goric)) {
ll <- attr(goric, "loglik")
PT <- attr(goric, "penalty")
result.goric <- c(ll, PT, goric)
names(result.goric) <- c("Loglik", "Penalty", paste0(attr(goric, "type")))
if (attr(goric, "type") == "goric") {
cat("\nGeneralized order-restricted information criterion: \n")
} else if (attr(goric, "type") == "goricc") {
cat("\nSmall sample generalized order-restricted information criterion: \n")
} else if (attr(goric, "type") == "gorica") {
cat("\nGeneralized order-restricted information criteron approximation: \n")
} else if (attr(goric, "type") == "goricac") {
cat("\nSmall sample generalized order-restricted information criteron approximation: \n")
}
print(result.goric, digits = digits)
}
cat("\n")
message(x$messages$mix_weights)
cat("\n")
invisible(x)
}
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