search for: mcmcoprobit

Hi: Is there a R-function that can generate samples from the posterior distribution of an ordered logistic regression model (just like MCMCoprobit from MCMCpack in R). I will greatly appreciate some guidance in this regard. Thanks Reez

...ry fancy. You won't get mundane things like ordered probit off the shelf. (I will be very happy if someone will show how to use glm() to do a vanilla probit!) But you will get markov chain monte carlo for the ordered probit model! :-) It's cool. > help.search("ordered probit") MCMCoprobit(mcmcpack-0.4-8) Markov chain Monte Carlo for Ordered Probit Regression > library(MCMCpack) ## ## Markov chain Monte Carlo Package (MCMCpack) ## Copyright (C) 2003 Andrew D. Martin and Kevin M. Quinn ## Loading required package: coda Loading requir...

..._RANGE -c 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: u...

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 everyone, I am running an ordinal probit using the Bayesian MCMCpack and I am getting an error saying "attempt for find suitable starting values failed" Here is my code: > posterior <- MCMCoprobit(y ~ x1 + x2 + x3 + x4 + x5 + x6 + x7 + x8 +x9 + x10 + x11 + x12 +x13 , beta.start=c(-10, 0.05, 0.02, 0.04, 0.98, 0.61, -0.29, 0.91, -0.82, 1.34, 0.68, 0.57, 0.09, 0.5), mcmc=10000) Here is the error: Error in polr(ordered(Y) ~ new.X) : attempt for find suitable starting values failed I don't...

...e the influence of certain attributes on the individuals choices. Anyway ChoiceModelR and bayesm just provide multinomial choice models while I am seeking for an ordinal probit. My data however doesn't have any panel structure. I was also experimenting with Bayesian inference in example by the MCMCoprobit function in the MCMCpack package, but this function just simulates betas. I can't however, as far as I know, attribute them to certain individuals in the survey, which would be good. I would be very glad if somebody could give me a hint, sometimes already a catchword is helpful to google the co...

What is the current state of the R-art for ordered probit models, and more esoterically is there any available R strategy for ordered cauchit models, i.e. ordered multinomial alternatives with a cauchy link function. MCMC is an option, obviously, but for a univariate latent variable model this seems to be overkill... standard mle methods should be preferable. (??) Googling reveals that spss