I am running JAGS models through the R package runjags. I just updated to JAGS 4.0.0 from JAGS 3.4, and have noticed some unexpected behavior that seems to be related to the update.
First, when I run a model, I now get a warning message WARNING: Unused variable(s) in data table: followed by a list of data objects that are referenced in the model and provided as data. It doesn't seem to affect the results (but it is very puzzling). I have, however, noticed a few times while playing around with this that for some variables the posteriors were virtually identical to the priors (indicating that no updating occured). I can't seem to recreate the update failure right now, but below is a reproducible code example illustrating the odd warning message. The code example on the run.jags help page also produces the same warning.
Second, I thought I'd check to see if the same message pops up if I use the R package R2jags instead of runjags, but R2jags won't load because apparently rjags (one of the dependencies) is not compatible with JAGS 4.0 (its looking for JAGS 3.X). Also, in the runjags function run.jags, the argument method="rjags" doesn't seem to work anymore, but method="parallel" does work.
I'm using runjags_2.0.1-4 and R 3.2.2.
So my questions are:
1) Is rjags really incompatible with JAGS 4.0? The motivation to go to 4.0 was to use vectors as indices (see https://martynplummer.wordpress.com/2015/08/16/whats-new-in-jags-4-0-0-part-34-r-style-features/).
2) What is up with the unused variable(s) warning, and should I be concerned about it?
Thanks, Glenn
Code:
#--- GENERATE DATA ------------------------
rm(list=ls())
# Number of sites and observations per site
N <- 200
nobs <- 3
# generate covariates and standardize (where appropriate)
set.seed(123)
forest <- rnorm(N)
# relationship between occupancy and covariates
b0 <- 0.5
b.for <- 0.5
psi <- plogis(b0 + b.for*forest)
# draw occupancy for each site
z <- rbinom(n=N, size=1,prob=psi)
# specify detection probablility
p <- 0.5
pz <- p*z
# generate the observations
Y <- rbinom(n=N, size=nobs,prob=pz)
#---- BUGS model ------------------------
model1 <- "model {
for (i in 1:N){
logit(eta[i]) <- b0 + b.for*forest[i]
z[i] ~ dbern(eta[i])
pz[i] <- z[i]*p
y[i] ~ dbin(pz[i],nobs)
} #i
b0.0 ~ dunif(0,1)
b0 <- log(b0.0/(1-b0.0))
b.for ~ dnorm(0,0.01)
p ~ dunif(0,1)
}"
occ.data1 <-list(y=Y,N=N,nobs=nobs,forest=forest)
inits1 <- function(){list(b0.0=runif(1),b.for=rnorm(1),p=runif(1),z=as.numeric(Y>0))}
parameters1 <- c("b0","b.for","p")
#---- RUN MODEL ------------------------
library(runjags)
ni <- 2000
nt <- 1
nb <- 1000
nc <- 3
ad <- 100
out <- run.jags(model=model1,data=occ.data1,monitor=parameters1,n.chains=nc,inits=inits1,burnin=nb,
sample=ni,adapt=ad,thin=nt,modules=c("glm","dic"),method="parallel")
To answer your questions:
1) rjags and JAGS used linked (non-interchangable) versions, and CRAN systems are still using JAGS_3.4.0 so the version of rjags on CRAN matches. This will be updated soon, and in the meantime you can grab the correct version of rjags from the sourceforge page as @jbaums notes.
2) This is a helpful message from JAGS/rjags telling you that you have specified something as data that the model isn't using. Remember that variable names are case sensitive i.e.
library('runjags')
model <- "model {
m ~ dunif(-1000,1000)
#data# M
#inits# m
#monitor# m
}"
M <- 0
m <- list(-10, 10)
results <- run.jags(model, method="interruptible", n.chains=2)
results <- run.jags(model, method="rjags", n.chains=2)
... gives you a warning because M does not match m. Also note that the warning looks a bit different from the two function calls - in the first it comes half-way down the JAGS output and in the second it comes as a warning in R after the function is completed.
As for 'should I be concerned' - yes if you think these variables should be in your model. If you can't find the problem try posting the code you are using - it got cut off from your original post.
Matt