Nothing
progreport = function(r, p, a, b, d, f, env) {
if (env$gNIV > 0) {
paramRMS <- sqrt(mean(apply(trans(b, env), 1, function(x) x^2)))
avgVariance <- mean(apply(trans(b, env), 1, var))
} else {
paramRMS <- NA
avgVariance <- NA
}
if (env$verbose) {
cat(rep("\n", 128))
cat("-----------------------------------------------------------\n")
cat("Iteration: ", r, "\n", sep = "\t")
cat("-----------------------------------------------------------\n")
mstats <- data.frame(
` ` = c("RHO (Fixed):", "Acceptance Rate (Fixed):",
"RHO (Normal):", "Acceptance Rate (Normal):", "Parameter RMS:",
"Avg. Variance:", "Log-Likelihood:", "RLH:"), ` ` = as.character(NA),
check.names = FALSE, stringsAsFactors = FALSE)
if (env$gFIV > 0) {
mstats[1, 2] <- signif(env$rhoF, env$gSIGDIG)
mstats[2, 2] <- signif(env$acceptanceRateFPerc, env$gSIGDIG)
}
if (env$gNIV > 0) {
mstats[3, 2] <- signif(env$rho, env$gSIGDIG)
mstats[4, 2] <- signif(env$acceptanceRatePerc, env$gSIGDIG)
mstats[5, 2] <- signif(paramRMS, env$gSIGDIG)
mstats[6, 2] <- signif(avgVariance, env$gSIGDIG)
}
mstats[7, 2] <- signif(sum(log(p)), env$gSIGDIG)
mstats[8, 2] <- signif(mean(p^(1/env$TIMES)), env$gSIGDIG)
print(mstats[complete.cases(mstats), , drop = FALSE], right = TRUE, row.names = FALSE)
cat("\n-----------------------------------------------------------\n\n")
if (env$gFIV > 0) {
print(data.frame(`Fixed Parameters` = paste0(env$gVarNamesFixed, ":"), Estimate = signif(f, env$gSIGDIG), check.names = FALSE), row.names = FALSE)
cat("\n-----------------------------------------------------------\n\n")
}
if (env$gNIV > 0) {
print(data.frame(`Random Parameters` = paste0(env$gVarNamesNormal, ":"), Estimate = signif(a, env$gSIGDIG), check.names = FALSE), row.names = FALSE)
cat("\n-----------------------------------------------------------\n")
}
if (r > 1) {
tpi <- (Sys.time() - env$starttime)/env$gINFOSKIP
env$starttime <- Sys.time()
tleft <- (env$gNCREP + env$gNEREP * env$gNSKIP - r) * tpi
units(tleft) <- "mins"
cat("Time per iteration:", format(tpi, digits = 3))
cat("\n")
cat("Time to completion:", format(tleft, digits = 3))
cat("\n")
} else {
cat("Time per iteration: Calculating...")
cat("\n")
cat("Time to completion: Calculating...")
cat("\n")
}
cat("-----------------------------------------------------------\n")
if (env$gNIV > 0 & env$gFIV > 0) {
alphas <- c(r, a, f)
} else if (env$gNIV > 0) {
alphas <- c(r, a)
} else if (env$gFIV > 0) {
alphas <- c(r, f)
}
cr <- rainbow(length(alphas) - 1)
if (r == 1) {
xmax <- (env$gNCREP + env$gNEREP * env$gNSKIP) * 1.05
plot(x = 0, y = 0, main = "Markov Chains", xlim = c(0, xmax), ylim = c(-5, 5), pch = 20, xlab = "Iterations", ylab = "Utility", axes = FALSE, col = "white", cex = 0.5)
segments(env$gNCREP, -100, env$gNCREP, 100, col = "red", lty = 2, lwd = 2)
segments(0, 0, env$gNCREP + env$gNEREP * env$gNSKIP, 0, col = "gray", lty = 1, lwd = 1)
axis(1, at = seq(from = 0, to = env$gNCREP + env$gNEREP * env$gNSKIP, by = floor((env$gNCREP + env$gNEREP * env$gNSKIP)/10)))
axis(2, at = -100:100)
}
for (i in 2:length(alphas)) {
points(x = alphas[1], y = alphas[i], pch = 20, col = cr[i - 1], cex = 0.5)
}
Sys.sleep(0)
}
detail <- c(r, signif(sum(log(p)), env$gSIGDIG), signif(mean(p^(1/env$TIMES)),
env$gSIGDIG), signif(paramRMS, env$gSIGDIG), signif(avgVariance,
env$gSIGDIG),
if (env$gFIV > 0) {
signif(env$acceptanceRateFPerc, env$gSIGDIG)
} else {
NA
},
if (env$gNIV > 0) {
signif(env$acceptanceRatePerc, env$gSIGDIG)
} else {
NA
})
env$results[["iter.detail"]] <- rbind(env$results[["iter.detail"]], detail)
}
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