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...distributions.cc -o distributions.o [...etc. etc. All compilations are ok] g++ -o MCMCpack.so distributions.o ide.o la.o lecuyer.o MCMCdistn.o MCMCdynamicEI.o MCMCfactanal.o MCMCfcds.o MCMChierEI.o MCMCirt1d.o MCMClogit.o MCMCmetrop1R.o MCMCmixfactanal.o MCMCmnlMH.o MCMCmnlslice.o MCMCoprobit.o MCMCordfactanal.o MCMCpanel.o MCMCpoisson.o MCMCprobit.o MCMCprobitres.o MCMCregress.o MCMCrng.o MCMCtobit.o mersenne.o optimize.o rng.o smath.o stat.o -L/usr/lib/R/lib -lR /usr/lib/gcc-lib/i486-linux/3.3.5/../../../crt1.o(.text+0x18): In function `_start': ../sysdeps/i386/elf/start.S:98: undefined referen...

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. Maybe I am not able to read them very well, by the

Hi: I have been working in Item Response Theory, exactly, with Nominal Response Model (NRM). Exist in R a function for estimate parameter and ability from database for this Model?. Thank you, Xavier G. Ordóñez [[alternative HTML version deleted]]

Hello, I tryed to use the MCMC pack, particularly the function MCMCirtKd to simulate the posterior distribution in a multidimensional IRT model. The code I used is: posterior1 <- MCMCirtKd(Y, dimensions=2, item.constraints=list("V2"=list(3,0)), burnin = 1000, mcmc = 10000, thin=1, verbose = 1, seed = NA, alphabeta.start = NA, b0 = 0, B0=0, store.item = FALSE,