I was up till 4 am with this sucker trying to figure it out- I
thought i lost my mind/ screwed it up somehow. I guess it's nice to
know it really wasn't me. Though, I AM sad R is messing up- first
time in over 3 years, so I guess it isn't so bad. But timing
couldn't have been worse, as I have a conference coming up.
Thanks very much, Duncan! I am going to give that a whirl tomorrow!
On Mar 28, 2013, at 10:37 PM, Duncan Mackay wrote:
> Hi Nicole
>
> I just upgraded to 2.15.3 today
> I was just having similar problems with run.jags and it stopping
dead in its tracks with an error message pointing to somewhere else
>
> See
>
> ?run.jags
> and the second paragraph of it.
>
> I then got it to run using a run.jags script using Rterm and
saved the model.
> By accident I copied and pasted a script to R with run.jags in it
and it now runs.
>
> see also ?test.jags
>
> Do not know what will happen after a reboot.
>
>
> HTH
>
> Duncan
>
> Duncan Mackay
> Department of Agronomy and Soil Science
> University of New England
> Armidale NSW 2351
> Email: home: mac...@northnet.com.au
>
>
>
> At 10:24 29/03/2013, you wrote:
>> To be clear everything "runs" with no error message... the only
hint of a problem is at the end of the code: the plot will not fill
out/ it is empty.
>>
>> if anyone has any idea why something like this might happen, i
would greatly appreciate it... so i can handle it quickly.
>>
>> thanks in advance.
>> On Mar 28, 2013, at 7:55 PM, Nicole Ford wrote:
>>
>> > 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")
>> >
>> >
>> > ############################
>> >
>> >
>> >
>> >
>> > [[alternative HTML version deleted]]
>> >
>> > ______________________________________________
>> > R-help@r-project.org mailing list
>> > https://stat.ethz.ch/mailman/listinfo/r-help
>> > PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
>> > and provide commented, minimal, self-contained, reproducible code.
>>
>> ______________________________________________
>> R-help@r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
