lqa: Penalized Likelihood Inference for GLMs

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.

Version: 1.0-3
Published: 2012-10-29
Author: Jan Ulbricht
Maintainer: Jan Ulbricht <jan.ulbricht at stat.uni-muenchen.de>
License: GPL-2
NeedsCompilation: no
CRAN checks: lqa results


Reference manual: lqa.pdf
Package source: lqa_1.0-3.tar.gz
Windows binaries: r-devel: lqa_1.0-3.zip, r-release: lqa_1.0-3.zip, r-oldrel: lqa_1.0-3.zip
OS X Snow Leopard binaries: r-release: lqa_1.0-3.tgz, r-oldrel: lqa_1.0-3.tgz
OS X Mavericks binaries: r-release: lqa_1.0-3.tgz
Old sources: lqa archive

Reverse dependencies:

Reverse imports: SparseLearner
Reverse suggests: catdata, mlr