Nothing
print.summary.dglm <- function(x, ..., digits = NULL, quote = TRUE, prefix = "", residuals = FALSE)
{
# Print summary of double glm
# GKS 7 Jan 98
#
xd <- x$dispersion.summary
x$dispersion.summary <- NULL
if (is.null(digits))
digits <- options()$digits
else {
old.digits <- options(digits = digits)
on.exit(options(old.digits))
}
cat("\nCall: ")
print(x$call)
#
# Mean submodel
#
# cat("\nMEAN MODEL")
nas <- x$nas
coef <- x$coef
correl <- x$correl
if (any(nas)) {
nc <- length(nas)
cnames <- names(nas)
coef1 <- array(NA, c(nc, 3), list(cnames, dimnames(coef)[[2]]))
coef1[!nas, ] <- coef
coef <- coef1
if (!is.null(correl)) {
correl1 <- matrix(NA, nc, nc, dimnames = list(cnames, cnames)
)
correl1[!nas, !nas] <- correl
correl <- correl1
}
}
dresid <- x$deviance.resid
n <- length(dresid)
rdf <- x$df[2]
if (residuals) {
if (rdf > 5) {
cat("Deviance Residuals:\n")
rq <- quantile(as.vector(dresid))
names(rq) <- c("Min", "1Q", "Median", "3Q", "Max")
print(rq, digits = digits)
}
else if (rdf > 0) {
cat("Deviance Residuals:\n")
print(dresid, digits = digits)
}
}
if (any(nas))
cat("\nMean Coefficients: (", sum(nas),
" not defined because of singularities)\n", sep = "")
else cat("\nMean Coefficients:\n")
print(coef, digits = digits)
cat(paste("(Dispersion Parameters for", x$family$family,
"family estimated as below", ")\n"))
int <- attr(x$terms, "intercept")
if (is.null(int))
int <- 1
cat("\n Scaled Null Deviance:", format(round(x$null.deviance, digits)), "on", n -
int, "degrees of freedom\n")
cat("Scaled Residual Deviance:", format(round(x$deviance, digits)), "on", round(
rdf, digits), "degrees of freedom\n")
# cat("\nNumber of Fisher Scoring Iterations:", format(trunc(x$iter)), "\n")
if (!is.null(correl)) {
p <- dim(correl)[2]
if (p > 1) {
cat("\nCorrelation of Coefficients:\n")
ll <- lower.tri(correl)
correl[ll] <- format(round(correl[ll], digits))
correl[!ll] <- ""
print(correl[-1, -p, drop = FALSE], quote = FALSE, digits = digits)
}
}
#
# Dispersion submodel
#
nas <- xd$nas
coef <- xd$coef
correl <- xd$correl
if (any(nas)) {
nc <- length(nas)
cnames <- names(nas)
coef1 <- array(NA, c(nc, 3), list(cnames, dimnames(coef)[[2]]))
coef1[!nas, ] <- coef
coef <- coef1
if (!is.null(correl)) {
correl1 <- matrix(NA, nc, nc, dimnames = list(cnames, cnames)
)
correl1[!nas, !nas] <- correl
correl <- correl1
}
}
dresid <- xd$deviance.resid
n <- length(dresid)
rdf <- xd$df[2]
if (residuals) {
if (rdf > 5) {
cat("Deviance Residuals:\n")
rq <- quantile(as.vector(dresid))
names(rq) <- c("Min", "1Q", "Median", "3Q", "Max")
print(rq, digits = digits)
}
else if (rdf > 0) {
cat("Deviance Residuals:\n")
print(dresid, digits = digits)
}
}
if (any(nas))
cat("\nDispersion Coefficients: (", sum(nas),
" not defined because of singularities)\n", sep = "")
else cat("\nDispersion Coefficients:\n")
print(coef, digits = digits)
cat(paste("(Dispersion parameter for", xd$family$family,
"family taken to be", format(round(xd$dispersion, digits)), ")\n"))
int <- attr(xd$terms, "intercept")
if (is.null(int))
int <- 1
cat("\n Scaled Null Deviance:", format(round(xd$null.deviance, digits)), "on", n -
int, "degrees of freedom\n")
cat("Scaled Residual Deviance:", format(round(xd$deviance, digits)), "on", round(
rdf, digits), "degrees of freedom\n")
# cat("\nNumber of Fisher Scoring Iterations:", format(trunc(xd$iter)), "\n")
if (!is.null(correl)) {
p <- dim(correl)[2]
if (p > 1) {
cat("\nCorrelation of Coefficients:\n")
ll <- lower.tri(correl)
correl[ll] <- format(round(correl[ll], digits))
correl[!ll] <- ""
print(correl[-1, -p, drop = FALSE], quote = FALSE, digits = digits)
}
}
#
# Overall iteration
#
cat("\nMinus Twice the Log-Likelihood:", format(round(x$m2loglik, digits)), "\n")
cat("Number of Alternating Iterations:", format(trunc(x$outer.iter)), "\n")
invisible(NULL)
}
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