I'm using the package R2jags in R, which uses the
parameters.to.save argument to specify parameters. I'm interested in the statistical distinction between a stochastic node (e.g.,
obs ~ dnorm(0, 0.01), where
obs is not listed in parameters.to.save) vs a parameter (if
obs were a parameter to save). Is this merely a programatic distinction, detailing which nodes should be returned to the user? Or is there a statistical distinction?
I've been told that there is no difference other than what is saved for user output. However, it seems plausible that there may be a statistical distinction, whereby parameters can have their distribution influenced by data, whereas the distribution of a stochastic node does not change with data.
I would experiment with this, but the only way I know how to track the value of a stochastic node in the model is to specify it as a parameter. You can see the conflict (although there is likely a more clever way to infer the effect that I haven't considered).
I realize this may ultimately be a programming issue, but I'm asking here because I'm really only concerned with the statistical interpretation/ distinction between a stochastic node and a parameter. I've read through the manual several times, and it's still a bit murky for me.