Generalized Additive Models for Location, Scale and Shape

London Metropolitan University

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Abstract

Summary A general class of statistical models for a univariate response variable is presented which we call the generalized additive model for location, scale and shape (GAMLSS). The model assumes independent observations of the response variable y given the parameters, the explanatory variables and the values of the random effects. The distribution for the response variable in the GAMLSS can be selected from a very general family of distributions including highly skew or kurtotic continuous and discrete distributions. The systematic part of the model is expanded to allow modelling not only of the mean (or location) but also of the other parameters of the distribution of y, as parametric and/or additive…

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Topics & keywords

Keywords
  • Generalized additive model
  • Mathematics
  • Additive model
  • Nonparametric statistics
  • Statistics
  • Univariate
  • Parametric statistics
  • Skew
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