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

  • D. Mikis Stasinopoulos
  • Robert A. Rigby
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    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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    Article provided by American Statistical Association in its journal Journal of Statistical Software.

    Volume (Year): 23 ()
    Issue (Month): i07 ()
    Pages:

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    Handle: RePEc:jss:jstsof:23:i07
    Contact details of provider: Web page: http://www.jstatsoft.org/

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    1. R. A. Rigby & D. M. Stasinopoulos, 2005. "Generalized additive models for location, scale and shape," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 54(3), pages 507-554.
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