Nothing
summary.glmRob <- function(object, correlation = TRUE, ...)
{
coef <- object$coef
resid <- object$residuals
dresid <- residuals(object, "deviance")
n <- length(resid)
p <- object$rank
if(is.null(p))
p <- sum(!is.na(coef))
if(!p) {
warning("This model has zero rank --- no summary is provided")
return(object)
}
nsingular <- length(coef) - p
rdf <- object$df.resid
if(is.null(rdf))
rdf <- n - p
family.name <- family(object)$family
dispersion <- 1
names(dispersion) <- family.name
covun <- object$cov
var <- diag(covun)
nas <- is.na(coef)
cnames <- names(coef[!nas])
coef <- matrix(rep(coef[!nas], 4), ncol = 4)
dimnames(coef) <- list(cnames, c("Estimate", "Std. Error", "z value", "Pr(>|z|)"))
coef[, 2] <- sqrt(var)
coef[, 3] <- coef[, 1]/coef[, 2]
coef[, 4] <- 2 * pnorm(-abs(coef[, 3]))
if(correlation) {
cor <- covun
for(i in 1:nrow(cor)) {
if (var[i]<1.e-10) {
str <- paste("Variance number",i,"smaller than 1.e-10",
"(set to 1.e-10)")
print(str)
}
cor[i,1:i] <- cor[i,1:i]/sqrt(var[i]*var[1:i])
cor[1:i,i] <- cor[i,1:i]
}
dimnames(cor) <- list(cnames, cnames)
}
else
cor <- NULL
dimnames(covun) <- list(cnames, cnames)
ocall <- object$call
if(!is.null(form <- object$formula)) {
if(is.null(ocall$formula))
ocall <- match.call(get("glm"), ocall)
ocall$formula <- form
}
ans <- list(call = ocall, terms = object$terms, coefficients = coef,
dispersion = dispersion, df = c(p, rdf), deviance.resid = dresid,
cov.unscaled = covun, correlation = cor, deviance = deviance(object),
null.deviance = object$null.deviance, iter = object$iter, nas=nas)
oldClass(ans) <- "summary.glmRob"
ans
}
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