Let's maybe back up a bit on this. You said you are interested in
learning about the application of the Gibbs sampler for IRT models. I
don't think opening the C++ code would be the best approach for this.
Let me recommend the following article
Patz, R. J., and Junker, B. W. (1999). A straightforward approach
to Markov chain Monte Carlo for item response models. Journal of
Educational and Behavioral Statistics, 24, 146-178.
This will give you what you need to know. Richard Patz also developed a
program written in S that follows the models presented in the article.
You can find this somewhere on the statlib cmu website. Also, I don't
know how mcmcirt works under the hood exactly, but Gibbs sampler is a
special case of the MH algorithm when the acceptance rate is 1.
Harold
> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of
> Mariagiulia Matteucci
> Sent: Friday, August 11, 2006 5:55 AM
> To: Barry Rowlingson
> Cc: r-help at stat.math.ethz.ch
> Subject: Re: [R] about MCMC pack again...
>
> Hello, I am using Windows, I tried to use th File Search and
> also the Windows Grep but I cannot find any file! In the list
> you showed me there are some useful , I really don't know how
> can I find them! I tried in the R folder, src folder, MCMC
> pack folder and I dowloaded the .tar file about MCMC pack
> where there are the codes, I really don't know what to do!
>
> Mariagiulia
>
>
> On Aug 11, 2006 10:51 AM, Barry Rowlingson
> <B.Rowlingson at lancaster.ac.uk> wrote:
>
> > Mariagiulia Matteucci wrote:
> > > Hello, thank you very much for your previous answers
> about the C++
> > > code.
> > > I am interested in the application of the Gibbs Sampler
> in the IRT
> > > models, so in the function MCMCirt1d and MCMCirtkd. I've
found the
> > > C++
> > > source codes, as you suggested, but I cannot find
> anything about the
> > > Gibbs Sampler. All the files are for the Metropolis algorithm.
> >
> > $ cd MCMCpack/
> > $ grep -ir gibbs .
> >
> > produces loads of output, including:
> >
> > ./src/MCMCfactanal.cc: } // end Gibbs loop
> > ./src/MCMChierEI.cc:// and slice sampling and Gibbs
> sampling to sample
> > from the posterior
> > ./src/MCMCirt1d.cc: } // end Gibbs loop
> > ./src/MCMCmixfactanal.cc: // Gibbs Sampler //
> > ./src/MCMCmixfactanal.cc: } // end Gibbs loop
> > ./src/MCMCoprobit.cc: // Gibbs loop
> > ./src/MCMCordfactanal.cc: // Gibbs Sampler //
> ./src/MCMCpanel.cc://
> > simulate from posterior density and return a Gibbs by parameters
> > matrix
> > ./src/MCMCpanel.cc: const int* burnin, const int* gibbs, const
> > int* thin,
> > ./src/MCMCpanel.cc: int Mgibbs = gibbs[0];
> > ./src/MCMCpanel.cc: int Mtotiter = Mburnin + Mgibbs;
> > ./src/MCMCpanel.cc: Matrix<double>
beta_holder(Mgibbs/Mthin,Mp);
> > ./src/MCMCpanel.cc: Matrix<double>
D_holder(Mgibbs/Mthin,Mq*Mq);
> > ./src/MCMCpanel.cc: Matrix<double> sigma2_holder(Mgibbs/Mthin,
1);
> > ./src/MCMCpanel.cc: // gibbs loop
> > ./src/MCMCregress.cc: // Gibbs sampler
> > ./src/MCMCregress.cc: // second set of Gibbs scans
> > ./src/MCMCSVDreg.cc: /////////////////// Gibbs sampler
> > ///////////////////
> >
> > Perhaps some of these are useful?
> >
> > For your info, I know nothing about MCMCpack, I just know
> how to use
> > grep to search for things. If you are on Windows, you can
> probably use
> > the Windows File Explorer Search option to look for it. But give me
> > grep anyday...
> >
> > Barry
> >
>
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