Hi: I sent you an email earlier privately. why you keep sending the same email over and over is not clear to me. ? the package by rossi et al, called "bayesm", has a function in it that supposedly does what you want. I don't know the details of the function because I was using their package for something else. the textbook associated with the package is difficult to follow ( just my opinion of course. someone else may love it ) but might be worth purchasing for understanding purposes because there's is a bayesian probit example in the text. that's all I can tell you so it's probably best to stop sending the same email over and over again.
On Tue, May 8, 2012 at 2:48 PM, rajeshpaleti <durgarajesh...@gmail.com>wrote: > Hi All, > > Sorry for posting the same question again. I was not sure if the message > was > sent initially since it was my first post the forum. > > Can the MNP package available in R be used to analyze panel data as well? > > i.e., if there are 3 observed discrete choices for three time periods for > the same individual , can i estimate a panel multinomial probit model which > allows correlated errors across time periods and individual heterogeneity > (random coefficients) using the MNP package? > > In the case that it doesn't work, is there any other Bayesian inference > based R package for estimating panel MNP models? > > Thanks, > Rajesh > > -- > View this message in context: > http://r.789695.n4.nabble.com/Panel-MNP-tp4618340.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > R-help@r-project.org 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. > [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org 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.
