Description: Local Polynomial Regression with Ridging.

Packaged: Mon May  2 17:35:28 2005; maechler

Packaged: Mon Jun 25 09:32:40 2007; maechler

Title: Penalized Likelihood Inference for GLMs
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.

Description: Fit quantile regression models for independent and
Packaged: 2012-04-29 15:25:37 UTC; Marco Geraci

Packaged: 2012-05-30 18:49:33 UTC; Marco Geraci

Packaged: 2012-09-15 06:39:54 UTC; Marco Geraci

Packaged: 2013-04-30 11:37:28 UTC; Marco Geraci

Description: Fit quantile regression models for independent and hierarchical data
Packaged: 2014-01-09 10:03:36 UTC; Marco Geraci

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

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

Description: Functions to fit quantile regression models for hierarchical
data (2-level nested designs) as described in Geraci and
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.

Packaged: 2014-05-01 12:32:06 UTC; Marco Geraci

Title: Robust Linear Quantile Regression
Author: Christian E. Galarza, Luis Benites, Victor H. Lachos
Imports: graphics, stats, ghyp, spatstat
Description: 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.