Nothing
print.BayesSAE <-
function(x, digits = max(3, getOption("digits") - 3), ...)
{
cat("\nCall:", deparse(x$call, width.cutoff = floor(getOption("width") * 0.85)), "", sep = "\n")
m <- x$m
p <- x$p
beta <- as.matrix(x[[1]][,(m+1):(m+p)])
beta <- colMeans(beta)
if(length(beta)) {
cat(paste("Regression coefficients in the linking model:\n", sep = ""))
print.default(format(beta, digits = digits), print.gap = 2, quote = FALSE)
cat("\n")
}
else cat("No coefficients in the linking model \n\n")
invisible(x)
}
summary.BayesSAE <-
function(object, HB = TRUE, ...)
{
## prediction
m <- object$m
innov <- object$innov
subset <- object$subset
if ((HB) && object$type != "UFH" && object$type != "UYC"){
theta <- object$HB
object$HB = TRUE
}
else{
theta <- colMeans(as.matrix(object[[1]][,1:m]))
object$HB <- FALSE
}
object$theta <- theta
## extend coefficient table
p <- object$p
cf <- cbind(summary(object[[1]])[[1]][(m+1):(m+p), 1:2], summary(object[[1]])[[2]][(m+1):(m+p), c(1,5)])
object$cf <- cf
## sampling variance
if (innov == "t"){
sig2 <- cbind(summary(object[[1]])[[1]][(m+p+2):(2*m+p+1), 1:2],
summary(object[[1]])[[2]][(m+p+2):(2*m+p+1), c(1,5)])
object$sig2 <- sig2
}
## residual standard error
sigv <- c(summary(object[[1]])[[1]][m+p+1,1:2], summary(object[[1]])[[2]][m+p+1, c(1,5)])
object$sigv <- sigv
## delete some slots
object$mcmc <- NULL
## return
class(object) <- "summary.BayesSAE"
object
}
print.summary.BayesSAE <-
function(x, digits = max(3, getOption("digits") - 3), ...)
{
cat("\nCall:", deparse(x$call, width.cutoff = floor(getOption("width") * 0.85)), "", sep = "\n")
type <- x$type
if (type == "FH")
Type <- "Basic Fay-Herriort Model"
else if (type == "YC")
Type <- "You-Chanpman Model"
else if (type == "UFH")
Type <- "Unmatched Fay-Herriort Model"
else if (type == "UYC")
Type <- "Unmatched You-Chapman Model"
else if (type == "SFH")
Type <- "CAR Area-Level Fay-Herriot Model"
else
Type <- "CAY Area-Level You-Chapman Model"
cat(Type, "\n")
name <- names(x$mf[1,])[1]
p <- x$p
m <- x$m
cat(paste("Sampling model: ", name, " ~ theta\n", sep = ""))
name <- names(x$mf[1,])[2:(p)]
if (x$tran == "F")
cat("Linking model: theta ~ ")
else if (x$tran == "log")
cat("Linking model: log(theta) ~ ")
else
cat("Linking model: logit(theta) ~ ")
cat(sprintf("%s +%s", name[1:(p-2)], ""), name[p-1])
if (x$spatial)
cat(" with spatial random effect\n")
else
cat("\n")
if (x$HB)
cat("\nRao-Blackwellization of theta's based on the simulation:\n")
else
cat("\nPosterior mean of theta's based on the simulation:\n")
print(structure(round(as.vector(x$theta), digits = digits), .Names = 1:m))
cat(paste("\nCoefficients in the linking model:\n", sep = ""))
printCoefmat(x$cf, digits = digits, signif.legend = FALSE)
if (x$innov == "t") {
cat(paste("\nSampling variance in the sampling model:\n", sep = ""))
printCoefmat(x$sig2, digits = digits, signif.legend = FALSE)
}
cat(paste("\nVariance of residual in the linking model:\n", sep = ""))
sigv <- matrix(x$sigv, c(4, 1))
row.names(sigv) <- c("Mean", "SD", "2.5%", "97.5")
printCoefmat(t(sigv), digits = digits, signif.legend = FALSE)
cat("\nDIC:", x$DIC, "\n")
invisible(x)
}
MCMC <-
function(object, ...){
result <- object$mcmc
return(result)
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.