This is a major revision, with two additional models included. 1) Multiresponse regression - family="mgaussian" Here we have a matrix of M responses, and we fit a series of linear models in parallel. We use a group-lasso penalty on the set of M coefficients for each variable. This means they are all in or out together
2) family="multinomial, type.multinomial="grouped" Same story = multinomial regression, but now the group lasso penalty ensures all the coefficients are in or out for each class at the same time. We have left the default as type.multinomial="ungrouped" because currently this grouped version is about 10 times slower. We will be looking to improve this aspect. Thanks to Noah Simon for his work on developing the algorithms for both these options. A report is in the works. ---------------------------------------------------------------------------------------- Trevor Hastie has...@stanford.edu Professor, Department of Statistics, Stanford University Phone: (650) 725-2231 Fax: (650) 725-8977 URL: http://www.stanford.edu/~hastie address: room 104, Department of Statistics, Sequoia Hall 390 Serra Mall, Stanford University, CA 94305-4065 -------------------------------------------------------------------------------------- [[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.
