Hi All, I have a set of features of size p and I would like to separate my feature space into two sets so that p = p1 + p2, p1 is a set of features and p2 is another set of features and I want to fit a glm model for each sets of features separately. Then I want to combine the results of two glm models with a parameter beta. For example, beta * F(p1) + (1-beta) * F(p2) where F(p1) is a learned model for feature set p1 and F(p2) is the learned model for feature set p2. Is there any way to do that in R?
There is a package called mixtools which can fit a mixture of two regression models but it does not separate the features. I would also like to separate features and fit a model for each feature set and then combine them. Thanks, Andra ______________________________________________ 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.
