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.

Install the latest version of this package by entering the following in R:
install.packages("lqa")
AuthorJan Ulbricht
Date of publication2012-10-29 08:59:07
MaintainerJan Ulbricht <jan.ulbricht@stat.uni-muenchen.de>
LicenseGPL-2
Version1.0-3

View on CRAN

Functions

adaptive.lasso Man page
aic.loss Man page
ao Man page
bic.loss Man page
bridge Man page
cv.lqa Man page
cv.nng Man page
dev.loss Man page
enet Man page
ForwardBoost Man page
fused.lasso Man page
GBlockBoost Man page
gcv.loss Man page
genet Man page
get.Amat Man page
icb Man page
lambda.check Man page
lasso Man page
licb Man page
lqa Man page
lqa.control Man page
lqa.default Man page
lqa.formula Man page
lqa-package Man page
lqa.update2 Man page
nng.update Man page
nnls Man page
nnls2 Man page
oscar Man page
penalreg Man page
penalty Man page
plot.lqa Man page
predict.lqa Man page
print.cv.lqa Man page
print.penalty Man page
print.pred.lqa Man page
print.summary.lqa Man page
ridge Man page
scad Man page
squared.loss Man page
summary.lqa Man page
weighted.fusion Man page

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

Please suggest features or report bugs with the GitHub issue tracker.

All documentation is copyright its authors; we didn't write any of that.