[R-pkgs] glmnet_1.8-4 on CRAN

[Trevor Hastie]

This version has some minor bug fixes, plus some new features.

* The exact=TRUE option in predict and coef methods now works.

In earlier versions of glmnet, if you supplied a value of s different from the 
sequence of lambdas used to compute the fit, predict used interpolation.
This is exact for lasso (alpha=1) and family="gaussian", and an approximation
otherwise.
Outside the range it used the closest member in the range.
The most frequent value requested was typically s=0,
and that was a) never in the range, and b) always a little off.

Now predict.glmnet returns the exact values

In case you missed earlier announcements, glmnet now has additional families.

* "mgaussian" is a multi-response gaussian model, that uses a group lasso penalty
for the set of coefficients for each predictor.

* For the type="multinomial" family, there is an additional argument 
type.multinomial=c("ungrouped","grouped") 
For the grouped cases, again a group lasso penalty is used on the set  of class coefficients
for a predictor.


Trevor Hastie

 ----------------------------------------------------------------------------------------
  Trevor Hastie                                   hastie at 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