# copy from R2WinBUGS
.decode.parameter.name <- function (a)
{
left.bracket <- regexpr("[[]", a)
if (left.bracket == -1) {
root <- a
dimension <- 0
indexes <- NA
}
else {
root <- substring(a, 1, left.bracket - 1)
right.bracket <- regexpr("[]]", a)
a <- substring(a, left.bracket + 1, right.bracket - 1)
indexes <- as.numeric(unlist(strsplit(a, ",")))
dimension <- length(indexes)
}
list(root = root, dimension = dimension, indexes = indexes)
}
jags.sims <- function (parameters.to.save, n.chains, n.iter, n.burnin, n.thin, DIC = TRUE)
{
#require(R2WinBUGS)
sims.files <- paste("CODAchain", 1:n.chains, ".txt", sep = "")
index <- read.table("CODAindex.txt", header = FALSE)#, sep = "\t")
parameter.names <- as.vector(index[, 1])
n.keep <- index[1, 3] - index[1, 2] + 1
n.parameters <- length(parameter.names)
n.sims <- n.keep * n.chains
sims <- matrix(, n.sims, n.parameters)
sims.array <- array(NA, c(n.keep, n.chains, n.parameters))
root.long <- character(n.parameters)
indexes.long <- vector(n.parameters, mode = "list")
for (i in 1:n.parameters) {
temp <- .decode.parameter.name(parameter.names[i])
root.long[i] <- temp$root
indexes.long[[i]] <- temp$indexes
}
n.roots <- length(parameters.to.save)
left.bracket.short <- as.vector(regexpr("[[]", parameters.to.save))
right.bracket.short <- as.vector(regexpr("[]]", parameters.to.save))
root.short <- ifelse(left.bracket.short == -1, parameters.to.save,
substring(parameters.to.save, 1, left.bracket.short - 1))
dimension.short <- rep(0, n.roots)
indexes.short <- vector(n.roots, mode = "list")
n.indexes.short <- vector(n.roots, mode = "list")
long.short <- vector(n.roots, mode = "list")
length.short <- numeric(n.roots)
for (j in 1:n.roots) {
long.short[[j]] <- (1:n.parameters)[root.long == root.short[j]]
length.short[j] <- length(long.short[[j]])
if (length.short[j] == 0) {
stop(paste("parameter", root.short[[j]], "is not in the model"))
}
else if (length.short[j] > 1) {
dimension.short[j] <- length(indexes.long[[long.short[[j]][1]]])
n.indexes.short[[j]] <- numeric(dimension.short[j])
for (k in 1:dimension.short[j]){
n.indexes.short[[j]][k] <- length(unique(unlist(lapply(indexes.long[long.short[[j]]],
.subset, k))))
}
length.short[j] <- prod(n.indexes.short[[j]])
if (length(long.short[[j]]) != length.short[j]){
stop(paste("error in parameter", root.short[[j]],
"in parameters.to.save"))
}
indexes.short[[j]] <- as.list(numeric(length.short[j]))
for (k in 1:length.short[j]){
indexes.short[[j]][[k]] <- indexes.long[[long.short[[j]][k]]]
}
}
}
rank.long <- unlist(long.short)
for (i in 1:n.chains) {
sims.i <- scan(sims.files[i], quiet = TRUE)[2 * (1:(n.keep *
n.parameters))]
sims[(n.keep * (i - 1) + 1):(n.keep * i), ] <- sims.i
sims.array[, i, ] <- sims.i
}
dimnames(sims) <- list(NULL, parameter.names)
dimnames(sims.array) <- list(NULL, NULL, parameter.names)
summary <- monitor(sims.array, n.chains, keep.all = TRUE)
last.values <- as.list(numeric(n.chains))
for (i in 1:n.chains) {
n.roots.0 <- if (DIC){ n.roots - 1}
else {n.roots}
last.values[[i]] <- as.list(numeric(n.roots.0))
names(last.values[[i]]) <- root.short[1:n.roots.0]
for (j in 1:n.roots.0) {
if (dimension.short[j] <= 1) {
last.values[[i]][[j]] <- sims.array[n.keep, i,
long.short[[j]]]
names(last.values[[i]][[j]]) <- NULL
}
else{
last.values[[i]][[j]] <- aperm(array(sims.array[n.keep,
i, long.short[[j]]], rev(n.indexes.short[[j]])),
dimension.short[j]:1)
}
}
}
sims <- sims[sample(n.sims), , drop = FALSE]
sims.list <- summary.mean <- summary.sd <- summary.median <- vector(n.roots,mode = "list")
names(sims.list) <- names(summary.mean) <- names(summary.sd) <- names(summary.median) <- root.short
for (j in 1:n.roots) {
if (length.short[j] == 1) {
sims.list[[j]] <- sims[, long.short[[j]]]
summary.mean[[j]] <- summary[long.short[[j]], "mean"]
summary.sd[[j]] <- summary[long.short[[j]], "sd"]
summary.median[[j]] <- summary[long.short[[j]], "50%"]
}
else {
sims.list[[j]] <- array(sims[, long.short[[j]]], c(n.sims, rev(n.indexes.short[[j]])))#, c(1, (dimension.short[j] + 1):2))
#sims.list[[j]] <- sims[, long.short[[j]]]
summary.mean[[j]] <- array(summary[long.short[[j]],"mean"],n.indexes.short[[j]])
summary.sd[[j]] <- array(summary[long.short[[j]],"sd"],n.indexes.short[[j]])
summary.median[[j]] <- array(summary[long.short[[j]],"50%"],n.indexes.short[[j]])
# temp2 <- dimension.short[j]:1
# sims.list[[j]] <- aperm(array(sims[, long.short[[j]]],
# c(n.sims, rev(n.indexes.short[[j]]))), c(1, (dimension.short[j] +
# 1):2))
# summary.mean[[j]] <- aperm(array(summary[long.short[[j]],
# "mean"], rev(n.indexes.short[[j]])), temp2)
# summary.sd[[j]] <- aperm(array(summary[long.short[[j]],
# "sd"], rev(n.indexes.short[[j]])), temp2)
# summary.median[[j]] <- aperm(array(summary[long.short[[j]],
# "50%"], rev(n.indexes.short[[j]])), temp2)
}
}
summary <- summary[rank.long,, drop = FALSE]
all <- list(n.chains = n.chains, n.iter = n.iter, n.burnin = n.burnin,
n.thin = n.thin, n.keep = n.keep, n.sims = n.sims, sims.array = sims.array[,
, rank.long, drop = FALSE], sims.list = sims.list,
sims.matrix = sims[, rank.long, drop = FALSE], summary = summary, mean = summary.mean,
sd = summary.sd, median = summary.median, root.short = root.short,
long.short = long.short, dimension.short = dimension.short,
indexes.short = indexes.short, last.values = last.values)
if (DIC) {
deviance <- all$sims.array[, , "deviance", drop = FALSE]
dimnames(deviance) <- NULL
dim(deviance) <- dim(deviance)[1:2]
# Modified by GB to change pD to pV
pV <- numeric(n.chains)
DIC <- numeric(n.chains)
for (i in 1:n.chains) {
pV[i] <- var(deviance[, i])/2
DIC[i] <- mean(deviance[, i]) + pV[i]
}
all <- c(all, list(isDIC = TRUE, DICbyR = TRUE, pV = mean(pV),
DIC = mean(DIC)))
}
else {
all <- c(all, isDIC = FALSE)
}
all
}
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