I have a runjags object that has two chains that mixed very well (chains 1 and 3), and one that did not (chain 2). How can I go about trimming the runjags object to just contain chains 1 and 3?
Here is a reproducible example of generating a JAGS model using runjags (although, the chains here mix fine).
library(runjags)
#generate the data
x <- seq(1,10, by = 0.1)
y <- x + rnorm(length(x))
#write a jags model
j.model = "
model{
#this is the model loop.
for(i in 1:N){
y[i] ~dnorm(y.hat[i], tau)
y.hat[i] <- m*x[i]
}
#priors
m ~ dnorm(0, .0001)
tau <- pow(sigma, -2)
sigma ~ dunif(0, 100)
}
"
#put data in a list.
data = list(y=y, x=x, N=length(y))
#run the jags model.
jags.out <- run.jags(j.model,
data = data,
n.chains=3,
monitor=c('m'))
One way to achieve this is to convert the runjags object to a mcmc.list, then remove the chain using the following code:
trim.jags <- as.mcmc.list(jags.out)
trim.jags <- mcmc.list(trim.jags[[1]], trimjags[[3]])
However, once converted in this direction, the data cannot be put back into the runjags format. I would really like a solution that keeps the output in the runjags format, as my current workflows rely on that formatting generated by the runjags summary output.
Take a look at the (admittedly not very obviously named) divide.jags function:
jags_13 <- divide.jags(jags.out, which.chains=c(1,3))
jags_13
extend.jags(jags_13)
# etc
Hopefully this does exactly what you want.
Matt