Introduction

The GAMLSS software is implemented in a series of packages in the R language ((R Development Core Team, 2013), and it is available from CRAN the R library at http://www.r-project.org.

The themes in this page are

• Packages
• Manual and other help for the packages
• Downloading the extra R GAMLSS packages
• ACEGES and GAMLSS
• Third party GAMLSS packages for R

The GAMLSS software currently comprises of the following different packages:

* the original gamlss package for fitting GAMLSS (now depends on gamlss.dist and gamlss.data
* the gamlss.add experimental package for new additive terms.
* the gamlss.boot experimental package for bootstrapping centile curves (not in CRAN).
* the gamlss.cens package for fitting censored (interval) response variables.
* the gamlss.data package for all example data used in GAMLSS.
* the gamlss.demo package for demos using the R package rpanel.
* the gamlss.dist package for all gamlss.family distributions.
* the gamlss.mx package for fitting finite mixture distributions.
* the gamlss.nl package for fitting nonlinear models.
* the gamlss.rsm experimental package for fitting randomly stopped models (not in CRAN).
* the gamlss.sparse experimental package using sparse matrices (not general yet therefore not in CRAN).
* the gamlss.tr package for fitting truncated distributions.
* the gamlss.util package having functions not necessarily related to GAMLSS.

All the gamlss.family distributions are now implemented in the package gamlss.dist .

Note that dependencies of the packages have changed radically in version 3.0-0 and also for version 4.2-0.

The gamlss packages reference card is available here

Each package has its individual help files. Here is a list of what users may find useful.

• The second edition of the manual of the gamlss package in pdf form. This is a good starting point covering most of the topics of the original gamlss package but it is now dated since it was created in 2008.
• The Journal of Statistical Software which has a brief introduction to GAMLSS and shows how the models can be used in practice.
• Course notes from the Lancaster 2009 short course.

The following table shows packages which are not currently in CRAN :

The current GAMLSS packages

The ACEGES decision-support tools is an agent-based model for exploratory energy policy by means of controlled computational experiments. The ACEGES tool is designed to be the foundation for large custom-purpose simulations of the global energy system. GAMLSS is the back-end statistical model for the regression-based rules of the agents in ACEGES.

Webpage: ACEGES
Related papers: Voudouris (2011) and Jefferson and Voudouris (2011).

gamboostLSS – Boosting Methods for GAMLSS models.
Summary: The package provides boosting methods for fitting generalized additive models for location, scale and shape (GAMLSS) to potentially high dimensional data.
Authors: Benjamin Hofner ( email), Andreas Mayr ( email), Nora Fenske ( email) and Matthias Schmid ( email).
R-Forge page: http://r-forge.r-project.org/projects/gamboostlss/
Related paper: http://epub.ub.uni-muenchen.de/11938/1/TR098.pdf