Introduction

There are three books on GAMLSS.
The GAMLSS models are implemented in a series of packages in the R language (R Development Core Team, 2022), and they are available from CRAN the R library at http://www.r-project.org. For more recent versions look at GAMLSS Universe

 

 

Packages

The following is a list of different packages created from the gamlss team:

  • the original gamlss package for fitting GAMLSS (depends on gamlss.dist and gamlss.data)
  • the new gamlss2 package for fitting GAMLSS and its extensions.
  • the gamlss.add package for extra additive terms.
  • 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.foreach package for parallel computing using foreach.
  • the gamlss.ggplots package for diagnostic and interpretation graphics. It is design to work with both gamlss and gamlss2 created objects. More information about the functions in the package can be found HERE
  • the gamlss.prepdata a package for preliminary data analysis or preparing data to fit a GAMLSS model. More information about the functions in the package can be found HERE
  • the gamlss.inf package for fitting zero inflated and zero adjusted continuous 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.spatial package for fitting Gaussian Markov random fields (MRF) models in GAMLSS.
  • the gamlss.tr package for fitting truncated distributions.
  • the gamlss.util package having functions not necessarily related to GAMLSS (not in CRAN).

Information how to use the packages can be found in the books and vignette page.

 

 

Third party GAMLSS related packages for R

  • gamboostLSS – Boosting Methods for GAMLSS models.
  • BAMLSS – Bayesian Additive Models for Location Scale and Shape (and Beyond)