Thanks for reply, Moshe. let's assume that the latent class model is the simplest one, 1 Y with gaussian distribution, 1 X, and 2 latent classes (A and B). Of course we can't assume that all my cases are from one class. Otherwise, why do I need to use latent class model? for each latent class, we have a model such that Y = Beta * X and beta is the coefficient.
i am not sure if this is specific enough. On Nov 8, 2007 8:28 PM, Moshe Olshansky <[EMAIL PROTECTED]> wrote: > Hi, > > Could you be more specific: what is your model? > Do you assume that ALL your observations are from > class j with probability Pj? What do you mean by > coefficients - distribution parameters? > If this is so then what you are doing is Bayes Rule > and it is all right (if F(X)i is the > probability/density of X under distribution i, where X > is the vector of all your observations). > > Regards, > > Moshe. > > > --- Wensui Liu <[EMAIL PROTECTED]> wrote: > > > Dear Listers, > > My post might be somewhat OT. > > Currently, I am trying to use flexmix to build a > > finite mixture model. > > For instance, I am getting the prior probability and > > coefficients for > > each latent class from training data. Is there a way > > to get the > > posterior probablity and prediction of a new > > dataset? > > What I am thinking is to apply the prior prob and > > coefficient from > > training set to testing data such that > > > > Post-Prob of Class j = Prior-Prob of Class j * F(X)j > > / sum(Prior-Prob > > of Class i * F(X)i) for i in [1, K] > > & > > prediction = sum(prediction for class i * post-prob) > > for i in [1, K]. > > > > However, I am not sure if this is correct. Any > > insight? > > Thanks a lot! > > > > -- > > =============================== > > WenSui Liu > > Statistical Project Manager > > ChoicePoint Precision Marketing > > (http://spaces.msn.com/statcompute/blog) > > > > ______________________________________________ > > 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. > > > > -- =============================== WenSui Liu Statistical Project Manager ChoicePoint Precision Marketing (http://spaces.msn.com/statcompute/blog) ______________________________________________ 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.
