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E-Jurnal Matematika, 2014 Poisson regression is a nonlinear regression that is often used to model count response variable and categorical, interval, or count regressor. This regression assumes equidispersion, i.e., the variance equals the mean.
NI MADE RARA KESWARI +2 more
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A linearization for stable and fast geographically weighted Poisson regression [PDF]
, 2023 Although geographically weighted Poisson regression (GWPR) is a popular regression for spatially indexed count data, its development is relatively limited compared to that found for linear geographically weighted regression (GWR), where many extensions ...
Nakaya, T. +4 more
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D-optimal designs for Poisson regression models [PDF]
, 2008 We consider the problem of finding an optimal design under a Poisson regression model with a log link, any number of independent variables and an additive linear predictor.
Woods, D.C. +3 more
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Evolutionary support vector regression for monitoring Poisson profiles
Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2023 Many researchers have shown interest in profile monitoring; however, most of the applications in this field of research are developed under the assumption of normal response variable.
A. Yeganeh +4 more
semanticscholar +1 more source
Zero-inflated generalized Poisson models with regression effects on the mean, dispersion and zero-inflation level applied to patent outsourcing rates [PDF]
, 2006 This paper focuses on an extension of zero-inflated generalized Poisson (ZIGP) regression models for count data. We discuss generalized Poisson (GP) models where dispersion is modelled by an additional model parameter.
Erhardt, Vinzenz +2 more
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Testing for zero-modification in count regression models [PDF]
, 2006 Count data often exhibit overdispersion and/or require an adjustment for zero outcomes with respect to a Poisson model. Zero-modified Poisson (ZMP) and zero-modified generalized Poisson (ZMGP) regression models are useful classes of models for such ...
Min, Aleksey, Czado, Claudia
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Axioms, 2022 The Poisson maximum likelihood (PML) is used to estimate the coefficients of the Poisson regression model (PRM). Since the resulting estimators are sensitive to outliers, different studies have provided robust Poisson regression estimators to alleviate ...
Issam Dawoud +3 more
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Modelling count data with overdispersion and spatial effects [PDF]
, 2005 In this paper we consider regression models for count data allowing for overdispersion in a Bayesian framework. Besides the inclusion of covariates, spatial effects are incorporated and modelled using a proper Gaussian conditional autoregressive prior ...
Gschlößl, Susanne, Czado, Claudia
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Modelling Generalized Poisson Regression in the Number of Dengue Hemorrhagic Fever (DHF) in East Nusa Tenggara [PDF]
E3S Web of Conferences, 2020 Regression analysis is an analysis used to model the relationship between the dependent variable (Y) and the independent variable (X). If the dependent variable is a discrete random variable, it is developed using the Poisson regression model.
Prahutama Alan +2 more
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AxiomsThis study introduces a new two-parameter Liu estimator (PMTPLE) for addressing the multicollinearity problem in the Poisson regression model (PRM). The estimation of the PRM is traditionally accomplished through the Poisson maximum likelihood estimator (
Mahmoud M. Abdelwahab +3 more
semanticscholar +1 more source