Results 31 to 40 of about 3,428,862 (283)
Efficient estimation of COM–Poisson regression and a generalized additive model [PDF]
Computational Statistics & Data Analysis, 2018 The Conway-Maxwell-Poisson (CMP) or COM-Poison regression is a popular model for count data due to its ability to capture both under dispersion and over dispersion. However, CMP regression is limited when dealing with complex nonlinear relationships. With today's wide availability of count data, especially due to the growing collection of data on human
Suneel Chatla, Galit Shmueli
openaire +3 more sources
Consistency and asymptotic normality of the maximum likelihood estimator in a zero-inflated generalized Poisson regression [PDF]
, 2005 Poisson regression models for count variables have been utilized in many applications. However, in many problems overdispersion and zero-inflation occur.
Min, Aleksey, Czado, Claudia
core +1 more source
Journal of New Theory, 2021 The Poisson regression model is widely used for count data. This model assumes equidispersion. In practice, equidispersion is seldom reflected in data. However, in real-life data, the variance usually exceeds the mean.
Burcu Durmuş, Öznur İşçi Güneri
doaj +1 more source
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
doaj +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
core +1 more source
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
core +1 more source
Model Generalized Poisson Regression (GPR) Pada Kasus Stunting Di Provinsi Nusa Tenggara Timur
Jurnal Diferensial, 2023 Stunting is a child development disorder due to chronic malnutrition and recurrent infections characterized by a height below average. The purpose of this study was to determine the Generalized Poisson Regression (GPR) model in stunting cases in East ...
Maria Febriana Lais +3 more
doaj +1 more source
Multivariate mixed Poisson Generalized Inverse Gaussian INAR(1) regression
Computational Statistics, 2022 AbstractIn this paper, we present a novel family of multivariate mixed Poisson-Generalized Inverse Gaussian INAR(1), MMPGIG-INAR(1), regression models for modelling time series of overdispersed count response variables in a versatile manner. The statistical properties associated with the proposed family of models are discussed and we derive the joint ...
Zezhun Chen +2 more
openaire +2 more sources
Can Generalized Poisson model replace any other count data models? An evaluation
Clinical Epidemiology and Global Health, 2021 Background: Count data represents the number of occurrences of an event within a fixed period of time. In count data modelling, overdispersion is inevitable.
Bijesh Yadav +6 more
doaj +1 more source
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
core +1 more source