Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13087/1056
Title: Penalized Splines Fitting for a Poisson Response Including Outliers
Authors: Kan Kılınç, Betül
Asfha, Huruy Debessay
Keywords: Poisson
Spline estimation
Deviance
Additive
Issue Date: 2019
Publisher: Univ Punjab
Abstract: There have been various studies in the literature on investigating the relationship between a count response and several covariates. Most researchers study count variables and use traditional methods (i.e. generalized linear models- GLM). However, GLM is limited when dealing with outliers and nonlinear relationships. Generalized Additive Models (GAM) is an extension of GLM, where the assumptions on the link functions and components are additive and smooth, respectively. Our aim is to propose a flexible extension of GLM and demonstrate the usefulness and performance of GAMs for the analysis of Poisson data set including outliers in the response variable through extensive Monte Carlo Simulations and using three applications.
URI: https://hdl.handle.net/20.500.13087/1056
ISSN: 1816-2711
2220-5810
Appears in Collections:Matematik Bölümü Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu
WoS İndeksli Yayınlar Koleksiyonu

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