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Questions about BUGS language for defining Bayesian models that can be run by the WinBUGS software package. It is advised to supplement your question with a reproducible BUGS example (http://stackoverflow.com/q/5963269).

2
votes
5000? That's nothing :-) In papers it is usual to use like 200,000. Variance parameters are always the worse for estimation. You have a huge autocorrelation in the chains - you should increase your th …
answered Jan 28 '13 by Curious
1
vote
1answer
I wonder, if I write - in JAGS, WinBUGS, or in a paper: x[] ~ dmulti(p[], N) is it the same as if I write: x[1] ~ dbin(p[1], N) x[2] ~ dbin(p[2], N) ... x[K] ~ dbin(p[K], N) or for (i in 1..K …
asked Nov 6 '14 by Curious
2
votes
For truncating, I use the operator I i.e.: x ~ dnorm(mean, tau)I(low, high)
answered Feb 3 '13 by Curious
1
vote
1answer
My breath was taken away by this. I tried to run my JAGS model with different number burn-in samples but it still takes the same amout of time!! n.iter n.burnin time saved iterations per cha …
asked Jan 30 '14 by Curious
5
votes
Just add the variable h to the list of the parameters to be monitored. If you are using package like R2WinBUGS, then add variable h to to the list passed to parameters.to.save argument to the bugs fun …
answered Jul 3 '12 by Curious
2
votes
I had exactly the same with specifying dgamma(0.001, 0.001) for WinBUGS! Jags can actually take it (and I recommend you to use Jags if you don't need advanced WinBUGS features; and even if you want … to use WinBUGS, it comes in handy for debugging, because Jags has much more comprehensible error reporting), but for WinBUGS, you must do: x[..] ~ dnorm(mean[..], tau) tau ~ dgamma(0.01, 0.01 …
answered Nov 26 '13 by Curious
-1
votes
1answer
It seems that WinBUGS has problems if it has only zero draws from one binomial distribution: 1. case - simple model for (i in 1:sites) { N[i] ~ dpois(lambda) for (j in 1:sample) { y … for case 1 wanted: Why this happens? Is it a WinBUGS bug? How can it be overriden? I have WinBUGS 1.4.3 (August 2007) with immortality patch installed. Below is complete reproducible code for R and …
asked Feb 14 '12 by Curious
1
vote
Yes, you can. In Bayesian tools, it is very easy to get predictions. In your design matrix, just add new rows, with response variable set to NA. You can see concrete example here.
answered Aug 20 '12 by Curious
4
votes
1answer
trees as a part of the model in WinBUGS/OpenBUGS/JAGS? Are there any such packages for these pieces of software? …
asked Nov 5 '14 by Curious
7
votes
2answers
I have my jags output object. In order to understand how MCMC coda chains work, I tried to see if first iteration in each MCMC chain is equal to the initial values supplied. And it is different! The i …
asked Oct 4 '12 by Curious
5
votes
1answer
I'm trying to compute a mixed model using jags (R2jags) and I got very strange divergence. The chains started so well, very well according to the results expected (also see lmer output of the same mod …
asked Oct 3 '12 by Curious
0
votes
0answers
I'm trying to do one-way ANOVA on uncertain (latent) input value YReal[i] (each input value is not exactly known, but it is given as normal distribution with mean Y[i] and standard deviation SE[i]). B …
asked Oct 15 '12 by Curious
6
votes
Parameters in linear predictor are t-distributed. When the number of records goes to infinity, it converges to normal distribution. So yes, normally it is considered correct to assume normal distribut …
answered Oct 14 '12 by Curious
2
votes
I think you are doing 3 mistakes: 1) in the frequentist example, you treat the data as if they were on the "normal" (logarithm) scale, while in the bayesian example, you treat them as on the "lognorm …
answered Jan 17 '13 by Curious