# R/Raftery.Diagnostic.R In LaplacesDemon: Complete Environment for Bayesian Inference

#### Documented in Raftery.Diagnostic

```###########################################################################
# Raftery.Diagnostic                                                      #
#                                                                         #
# The purpose of the Raftery.Diagnostic function is to perform MCMC       #
# diagnostics on an object of class demonoid.                             #
###########################################################################

Raftery.Diagnostic <- function(x, q=0.025, r=0.005, s=0.95, eps=0.001)
{
if(missing(x)) stop("x is a required argument")
if(!identical(class(x), "demonoid"))
stop("x must be an object of class demonoid.")
if(all(is.na(x\$Posterior2))) post <- x\$Posterior1
else post <- x\$Posterior2
Thinning <- x\$Thinning
resmatrix <- matrix(nrow=ncol(post), ncol=4,
dimnames=list(colnames(post),
c("M", "N", "Nmin", "I")))
phi <- qnorm(0.5 * (1 + s))
nmin <- as.integer(ceiling((q * (1 - q) * phi^2) / r^2))
if(nmin > nrow(post)) resmatrix <- c("Error", nmin)
else for (i in 1:ncol(post)) {
quant <- quantile(post[, i, drop=TRUE], probs=q)
dichot <- post[, i, drop=TRUE] <= quant
kthin <- 0
bic <- 1
while (bic >= 0) {
kthin <- kthin + Thinning
testres <- as.vector(Thin(dichot, By=kthin))
testres <- factor(testres, levels=c(FALSE,TRUE))
newdim <- length(testres)
testtran <- table(testres[1:(newdim - 2)],
testres[2:(newdim - 1)], testres[3:newdim])
testtran <- array(as.double(testtran), dim=dim(testtran))
g2 <- 0
for (i1 in 1:2) {
for (i2 in 1:2) {
for (i3 in 1:2) {
if(testtran[i1, i2, i3] != 0) {
fitted <- (sum(testtran[i1, i2, 1:2]) *
sum(testtran[1:2, i2, i3])) /
(sum(testtran[1:2, i2, 1:2]))
g2 <- g2 + testtran[i1, i2, i3] *
log(testtran[i1, i2, i3]/fitted) * 2
}}}}
bic <- g2 - log(newdim - 2) * 2
}
finaltran <- table(testres[1:(newdim - 1)], testres[2:newdim])
alpha <- finaltran[1, 2]/(finaltran[1, 1] + finaltran[1, 2])
beta <- finaltran[2, 1]/(finaltran[2, 1] + finaltran[2, 2])
tempburn <- log((eps * (alpha + beta))/max(alpha,
beta))/(log(abs(1 - alpha - beta)))
nburn <- as.integer(ceiling(tempburn) * kthin)
tempprec <- ((2 - alpha - beta) * alpha * beta * phi^2) /
(((alpha + beta)^3) * r^2)
nkeep <- as.integer(ceiling(tempprec) * kthin)
iratio <- (nburn + nkeep) / nmin
resmatrix[i, 1] <- nburn
resmatrix[i, 2] <- nkeep + nburn
resmatrix[i, 3] <- nmin
resmatrix[i, 4] <- signif(iratio, digits=3)
}
y <- list(params=c(q=q, r=r, s=s), resmatrix=resmatrix)
class(y) <- "raftery"
return(y)
}

#End
```

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LaplacesDemon documentation built on July 1, 2018, 9:02 a.m.