[R] about MCMC pack again...
matteucci at stat.unibo.it
Fri Aug 11 14:05:51 CEST 2006
thank you very much. By the way, I know the article but my interest is
more on the normal ogive model, and on the Inversion (probability
integral transformation) method applied to the Gibbs sampler.
If somebody knows something about it and about missing data in MCMC pack
in R, please let me know
On Aug 11, 2006 01:27 PM, "Doran, Harold" <HDoran at air.org> wrote:
> 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
> 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.
> > -----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;
> > > ./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
> > >
> > ______________________________________________
> > R-help at stat.math.ethz.ch mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide
> > http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
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