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

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Stasinopoulos, D. Mikis, Rigby, Robert A.·2007·Journal of Statistical Software

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.

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Metadata

Authors
Stasinopoulos, D. M., & Rigby, R. A.
Venue
Journal of Statistical Software
Published
2007
Volume
23
Issue
7
ISSN
1548-7660 (ISSN-L)
OpenAlex
W1507444366
Cited by
1,560
References
0
FWCI
24.82
Type
journal article
Language
en
Open access
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CoChat. (2026). Citation check: Generalized Additive Models for Location Scale and Shape (GAMLSS) in R. https://app.cochat.ai/papers/10.18637/jss.v023.i07
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Stasinopoulos, D. M., & Rigby, R. A. (2007). Generalized Additive Models for Location Scale and Shape (GAMLSS) in R. Journal of Statistical Software. https://doi.org/10.18637/jss.v023.i07

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