Last data update: 2014.03.03

lqa

Package: lqa
Type: Package
Title: Penalized Likelihood Inference for GLMs
Version: 1.0-3
Date: 2010-07-12
Author: Jan Ulbricht
Maintainer: Jan Ulbricht <jan.ulbricht@stat.uni-muenchen.de>
Description: This package provides some basic infrastructure and tools
to fit Generalized Linear Models (GLMs) via penalized
likelihood inference. Estimating procedures already implemented
are the LQA algorithm (that is where its name come from),
P-IRLS, RidgeBoost, GBlockBoost and ForwardBoost.
License: GPL-2
LazyLoad: yes
Packaged: 2012-10-29 08:59:07 UTC; ripley
Repository: CRAN
Date/Publication: 2012-10-29 08:59:07

● 0 images, 26 functions, 0 datasets
● Reverse Depends: 0

Install log

* installing to library '/home/ddbj/local/lib64/R/library'
* installing *source* package 'lqa' ...
** package 'lqa' successfully unpacked and MD5 sums checked
** R
** inst
** preparing package for lazy loading
** help
*** installing help indices
  converting help for package 'lqa'
    finding HTML links ... done
    ForwardBoost                            html  
    GBlockBoost                             html  
    adaptive.lasso                          html  
    ao                                      html  
    bridge                                  html  
    cv.lqa                                  html  
    cv.nng                                  html  
    enet                                    html  
    fused.lasso                             html  
    genet                                   html  
    get.Amat                                html  
    icb                                     html  
    lasso                                   html  
    licb                                    html  
    lqa-internal                            html  
    lqa-package                             html  
    lqa                                     html  
    lqa.control                             html  
    oscar                                   html  
    penalreg                                html  
    penalty                                 html  
    plot.lqa                                html  
    predict.lqa                             html  
    ridge                                   html  
    scad                                    html  
    weighted.fusion                         html  
** building package indices
** testing if installed package can be loaded
* DONE (lqa)
Making 'packages.html' ... done