Burkhardt Seifert <seifert@ifspm.unizh.ch> (S original);
Packaged for R by Martin Maechler
"lpridge" and "lpepa" provide local polynomial regression
algorithms including local bandwidth use.

Local Polynomial Regression with Ridging.

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.

Fit quantile regression models for independent and
hierarchical data

Fit quantile regression models for independent and hierarchical data

This is a collection of functions to fit quantile regression models for independent and hierarchical data.

stats, utils, nlme (>= 3.1-124), SparseGrid

Functions to fit quantile regression models for hierarchical
data (2-level nested designs) as described in Geraci and
Bottai (2014, Statistics and Computing) <doi:10.1007/s11222-013-9381-9>.
A vignette is given in Geraci (2014, Journal of Statistical Software)
<doi:10.18637/jss.v057.i13> and included in the package documents.
The packages also provides functions to fit quantile models for
independent	data and for count responses.

Christian E. Galarza, Luis Benites, Victor H. Lachos
It fits a robust linear quantile regression model using a new family of zero-quantile distributions for the error term.
This family of distribution includes skewed versions of the Normal, Student's t, Laplace, Slash and Contaminated Normal distribution.
It provides estimates and full inference. It also provides envelopes plots for assessing the fit and confidences bands when several quantiles are provided simultaneously.

It fits a robust linear quantile regression model using a new
family of zero-quantile distributions for the error term. This family of
distribution includes skewed versions of the Normal, Student's t, Laplace, Slash
and Contaminated Normal distribution. It provides estimates and full inference.
It also provides envelopes plots for assessing the fit and confidences bands
when several quantiles are provided simultaneously.