Generalized Additive Models for Location Scale and Shape (GAMLSS) in R

Generalized Additive Models for Location Scale and Shape (GAMLSS) in R

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 r...

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Bibliographic Details
Main Authors: D. Mikis Stasinopoulos, Robert A. Rigby
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2007-11-01
Series:Journal of Statistical Software
Subjects:
Box-Cox transformation
centile estimation
cubic smoothing splines
LMS method
negative binomial
non-normal
non-parametric
overdispersion
penalized likelihood
skewness and kurtosis
Online Access:http://www.jstatsoft.org/v23/i07/paper
Description
Summary: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.
ISSN:1548-7660

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