Nothing
`print.summary.hglm` <-
function(x, digits = 4, print.ranef = FALSE, ...) {
x$nRand <- cumsum(x$RandC)
cat("Call: \n")
print(x$call)
cat('\n----------\n')
cat("MEAN MODEL\n")
cat('----------\n')
cat("\n")
cat("Summary of the fixed effects estimates:\n")
cat("\n")
printCoefmat(x$FixCoefMat, digits = digits, P.values = TRUE, has.Pvalue = TRUE)
cat("Note: P-values are based on", x$devdf, "degrees of freedom\n")
if (!is.null(x$RandCoefMat)) {
if (length(x$RandC) == 1) {
cat("\n")
cat("Summary of the random effects estimates:\n")
cat("\n")
if (nrow(x$RandCoefMat) <= 5) {
print(round(x$RandCoefMat, digits))
} else if (print.ranef) {
print(round(x$RandCoefMat, digits))
} else {
print(round(x$RandCoefMat[1:3,], digits))
cat('...\n')
cat('NOTE: to show all the random effects, use print(summary(hglm.object), print.ranef = TRUE).\n')
}
} else {
for (J in 1:length(x$RandC)) {
cat("\n")
cat("Summary of the random effects estimates:\n")
cat("\n")
if (nrow(x$RandCoefMat[[J]]) <= 5) {
print(round(x$RandCoefMat[[J]], digits))
} else if (print.ranef) {
print(round(x$RandCoefMat[[J]], digits))
} else {
print(round(x$RandCoefMat[[J]][1:3,], digits))
cat('...\n')
cat('NOTE: to show all the random effects, use print(summary(hglm.object), print.ranef = TRUE).\n')
}
}
}
}
cat('\n')
cat("----------------\n")
cat("DISPERSION MODEL\n")
cat("----------------\n")
cat("\n")
if (x$Method == "REML"){
cat("-2*Log(Profile-Likelihood) =", round(-2*x$ProfLogLik, digits), "\n")
} else {
cat("NOTE: h-likelihood estimates through EQL can be biased.\n")
}
if (!is.null(x$varFix)) {
if (is.null(x$SummVC1)) {
cat("\n")
cat("Dispersion parameter held Constant at:", x$varFix, '\n')
} else {
cat("\n")
cat("Dispersion parameter for the mean model:\n")
print(x$varFix)
}
}
if (!is.null(x$SummVC1)) {
cat("\n")
cat("Model estimates for the dispersion term:\n")
cat("\nLink =", x$link.disp, "\n")
cat("\nEffects:\n")
print(round(x$SummVC1, digits))
cat("\n")
cat("Dispersion = 1 is used in Gamma model on deviances to calculate the standard error(s).")
}
cat('\n')
if (!is.null(x$varRanef)) {
cat("\n")
cat("Dispersion parameter for the random effects:\n")
print(x$varRanef, digits = digits)
cat("\n")
cat("Dispersion model for the random effects:\n")
cat("\nLink = log\n")
if (length(x$RandC) == 1) {
cat("\nEffects:\n")
cat(names(x$SummVC2), '\n')
if (is.null(x$CAR.tau) & is.null(x$SAR.tau)) {
print(round(x$SummVC2[[1]], digits))
} else if (!is.null(x$CAR.tau)) {
rownames(x$SummVC2[[1]]) <- c('1/CAR.tau', '-CAR.rho/CAR.tau')
print(round(x$SummVC2[[1]], digits))
cat('CAR.tau (estimated spatial variance component):', x$CAR.tau, '\n')
cat('CAR.rho (estimated spatial correlation):', x$CAR.rho, '\n')
} else {
rownames(x$SummVC2[[1]]) <- c('1/sqrt(SAR.tau)', '-SAR.rho/sqrt(SAR.tau)')
print(round(x$SummVC2[[1]], digits))
cat('SAR.tau (estimated spatial variance component):', x$SAR.tau, '\n')
cat('SAR.rho (estimated spatial correlation):', x$SAR.rho, '\n')
}
cat("\n")
} else {
ranefnames <- names(x$SummVC2)
cat("\nEffects:\n")
for (J in 1:length(x$RandC)) {
cat(ranefnames[J], '\n')
if (is.null(x$CAR.tau) & is.null(x$SAR.tau)) {
print(round(x$SummVC2[[J]], digits))
} else if (!is.null(x$CAR.tau)) {
if (x$call.rand.family[[J]]$family == 'CAR') {
rownames(x$SummVC2[[J]]) <- c('1/CAR.tau', '-CAR.rho/CAR.tau')
print(round(x$SummVC2[[J]], digits))
cat('CAR.tau (estimated spatial variance component):', x$CAR.tau, '\n')
cat('CAR.rho (estimated spatial correlation):', x$CAR.rho, '\n')
} else {
print(round(x$SummVC2[[J]], digits))
}
} else {
if (x$call.rand.family[[J]]$family == 'SAR') {
rownames(x$SummVC2[[J]]) <- c('1/sqrt(SAR.tau)', '-SAR.rho/sqrt(SAR.tau)')
print(round(x$SummVC2[[J]], digits))
cat('SAR.tau (estimated spatial variance component):', x$SAR.tau, '\n')
cat('SAR.rho (estimated spatial correlation):', x$SAR.rho, '\n')
} else {
print(round(x$SummVC2[[J]], digits))
}
}
cat("\n")
}
}
cat("Dispersion = 1 is used in Gamma model on deviances to calculate the standard error(s).\n")
}
cat("\n")
if (!is.null(x$likelihood)) {
cat("---------------\n")
cat("LOG-LIKELIHOODS\n")
cat("---------------\n")
cat("\n")
cat("h-likelihood:", x$likelihood$hlik, "\n")
cat("Adjusted profile likelihood", "\n")
cat(" Profiled over random effects:", x$likelihood$pvh, "\n")
cat(" Profiled over fixed and random effects:", x$likelihood$pbvh, "\n")
cat("Conditional AIC:", x$likelihood$cAIC, "\n")
cat("\n")
}
cat(x$Method, "estimation", x$converge, "in", x$iter, "iterations.\n")
if (!is.null(x$bad)) {
cat('\n!! Observation', x$bad, 'is too influential! Estimates are likely unreliable !!')
}
}
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