i am having problem running my own data.  yesterday it was working just fine.  today it is not.  this is the code i was using as an example to follow.  this code ALSO worked just fine yesterday, and is no longer working at all.  i suspect it is a problem with either my computer or the software, at this point.  if THIS won't even run....  something is wrong.

i can assure you this isn't HW....  i know dave, but i am no longer at UW-M and i have never learned HLMs and i am learning this on my own for my own research.

his code is here, along with data.  it is short, quick, etc.

http://www.quantoid.net/936/Lecture7.R

### R code from vignette source 'Lecture7.Rnw'

###################################################
### code chunk number 1: opts
###################################################
options(useFancyQuotes=F)


###################################################
### code chunk number 2: data1
###################################################
library(foreign)
therms <- na.omit(read.dta("http://quantoid.net/936/2008_difftherm.dta"))
unstate <- unique(therms[,1])
therms$numstate <- match(therms$state, unstate)
library(runjags)
dat <- dump.format(list(
	N = nrow(therms), J=length(unstate), 
	y = therms$difftherm, 
	numstate = therms$numstate
))


###################################################
### code chunk number 3: exchange
###################################################
exchange.mod <- "model{
	for(i in 1:N){
		y[i] ~ dnorm(mu, tau)
	}
	mu ~ dnorm(0,.001)
	tau ~ dgamma(.1,.1)
}"
exchange.out <- run.jags(exchange.mod, 
	data=dat, burnin=10000, sample=50000, 
	thin=5, monitor=c("mu", "tau"), 
	monitor.deviance=T, monitor.pd=T, 
	silent.jags=T)



###################################################
### code chunk number 4: exchange
###################################################
FE.mod <- "model{
	for(i in 1:N){
		y[i] ~ dnorm(mu[numstate[i]], tau[numstate[i]])
	}
	for(j in 1:J){
		mu[j] ~ dnorm(0,.001)
		tau[j] ~ dgamma(.1,.1)
	}
}"
FE.out <- run.jags(FE.mod, 
	data=dat, burnin=10000, sample=50000, 
	thin=5, monitor=c("mu", "tau"), 
	monitor.deviance=T, monitor.pd=T, 
	silent.jags=T)


###################################################
### code chunk number 5: exchange
###################################################
hier.mod <- "model{
	for(i in 1:N){
		y[i] ~ dnorm(mu[numstate[i]], tau[numstate[i]])
	}
	for(j in 1:J){
		mu[j] ~ dnorm(theta,nu)
		tau[j] ~ dgamma(a,b)
	}
	theta ~ dnorm(0,.01)
	nu ~ dgamma(.1,.1)
	a ~ dunif(0,1000)
	b ~ dunif(0,1000)
}"
hier.out <- run.jags(hier.mod, 
	data=dat, burnin=10000, sample=100000, 
	thin=10, monitor=c("mu", "tau", "theta", "nu", "a", "b"), 
	monitor.deviance=T, monitor.pd=T, 
	silent.jags=T)


###################################################
### code chunk number 6: sums
###################################################
hier.chains <- combine.mcmc(hier.out$mcmc)
FE.chains <- combine.mcmc(FE.out$mcmc)
exchange.chains <- combine.mcmc(exchange.out$mcmc)

mu.bar <- apply(FE.chains[, grep("mu\\[", colnames(FE.chains))], 2, mean)
mu.bar2 <- apply(hier.chains[, grep("mu\\[", colnames(hier.chains))], 2, mean)
ns <- aggregate(therms$numstate, list(therms$stateabb), length)
plot(mu.bar, mu.bar2, cex=sqrt(ns[,2])/3, 
	xlab = "FE mu[j]", 
	ylab = "Hierarchical mu[j]")
abline(a=0, b=1)


###################################################
### code chunk number 7: dotchart
###################################################
fe.mu <- FE.chains[,grep("mu\\[", colnames(FE.chains))]
fe.ci <- t(apply(fe.mu, 2, quantile, c(.5,.025,.975)))
rownames(fe.ci) <- unstate
fe.ci <- fe.ci[order(fe.ci[,1]), ]
dotchart(fe.ci[order(fe.ci[,1]),1], lcolor="white", pch=16, 
	xlim=range(c(fe.ci)))
segments(fe.ci[,2], 1:34, fe.ci[,3], 1:34)
mu.ci <- quantile(exchange.chains[,1], c(.5,.025,.975))
polygon(x=mu.ci[c(2,3,3,2)], 
	y = c(-1,-1,36,36), 
	col=rgb(128,128,128,100, maxColorValue=255), 
	border=NA)
abline(v=mu.ci[1], lty=2, lwd=2)
axis(4, at=1:34, labels=ns[match(rownames(fe.ci), ns[,1]),2], 
	cex.axis=.75, las=2)


###################################################
### code chunk number 8: femeans
###################################################
library(sm)
sm.density(mu.bar, model="normal")


############################




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