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]]
>
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