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) ______________________________________________ [email protected] 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.
