M. Stasinopoulos

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Generalized Additive Models for Location, Scale and Shape (GAMLSS) were introduced by Rigby and Stasinopoulos (2005). GAMLSS is a general framework for univariate regression type statistical problems. In GAMLSS the exponential family distribution assumption used in Generalized Linear Model (GLM) and Generalized Additive Model (GAM), (see Nelder and(More)
In this paper we h a ve proposed a class of Generalized Autoregressive M o v-ing Average GARMA models which extend univariate ARMA models to a non-Gaussian situation i.e. they extend the univariate Generalized Linear Model to incorporate time dependence in the observations. The simplicity of the tting algorithm within the iteratively reweighted least(More)
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