Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
[test by reto]
Authors: D. Mikis Stasinopoulos, Robert A. Rigby
Title: Generalized Additive Models for Location Scale and Shape (GAMLSS) in R
Abstract: GAMLSS is a general framework for fitting regression type models where the distribution of the response variable does not have to belong to the exponential family and includes highly skew and kurtotic continuous and discrete distribution. GAMLSS allows all the parameters of the distribution of the response variable to be modelled as linear/non-linear or smooth functions of the explanatory variables. This paper starts by defining the statistical framework of GAMLSS, then describes the current implementation of GAMLSS in R and finally gives four different data examples to demonstrate how GAMLSS can be used for statistical modelling.

Page views:: 50944. Submitted: 2007-07-19. Published: 2007-12-31.
Paper: Generalized Additive Models for Location Scale and Shape (GAMLSS) in R     Download PDF (Downloads: 53255)
gamlss.cens_1.7.0.tar.gz: R source package Download (Downloads: 2174; 9KB)
gamlss.dist_1.7-0.tar.gz: R source package Download (Downloads: 1942; 54KB)
gamlss.mx_1.7-0.tar.gz: R source package Download (Downloads: 1880; 20KB)
gamlss.nl_1.7-0.tar.gz: R source package Download (Downloads: 1904; 25KB)
gamlss.tr_1.7-0.tar.gz: R source package Download (Downloads: 1841; 7KB)
gamlss_1.7-0.tar.gz: R source package Download (Downloads: 2013; 2MB)
v23i07.R: R example scripts from the paper Download (Downloads: 3765; 7KB)

DOI: 10.18637/jss.v023.i07

This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.