Results 71 to 80 of about 824 (147)

A Stochastic Condensation Mechanism for Inducing Underdispersion in Count Models

, 2021
Chénangnon Frédéric Tovissodé, Romain Glèlè Kakaï   +1 more
openalex   +2 more sources

Stationary Underdispersed INAR(1) Models based on the Backward Approach

Revstat Statistical Journal
Most of the stationary first-order autoregressive integer-valued (INAR(1)) models in the literature have been developed using the idea of binomial thinning. Two approaches have been adopted to establish the distributional properties of a stationary INAR(
Emad-Eldin A. A. Aly, Nadjib Bouzar
doaj   +1 more source

CONWAY-MAXWELL POISSON REGRESSION MODELING OF INFANT MORTALITY IN SOUTH SULAWESI

Media Statistika
Overdispersion is a common problem in count data that can lead to inaccurate parameter estimates in Poisson regression models. Quasi-Poisson and negative binomial regressions are often used to address overdispersion but have limitations, especially with ...
Oktaviana Oktaviana, Wahidah Sanusi, Aswi Aswi, Sukarna Sukarna, Serifat Adedamola Folorunso   +4 more
doaj   +1 more source

Flexible models for non-equidispersed count data: comparative performance of parametric models to deal with underdispersion

, 2022
Douglas Toledo Batista, Cristiane Akemi Umetsu, António Fernando Monteiro Camargo, Idemauro Antônio Rodrigues de Lara   +3 more
openalex   +2 more sources

Negative Binomial Regression in Underdispersion(Case Study: Neonatal Mortality in Jambi City)

, 2022
Corry Sormin, Z Gusmanely
openalex   +2 more sources

Enhancing the accuracy of modeling highly multicollinear CO2 emission data using a novel generalized Poisson Liu regression method

AIP Advances
Count data often exhibit dispersion patterns that the standard Poisson regression model struggles to handle, particularly in cases of overdispersion or underdispersion. The generalized Poisson regression model (GPRM) provides a more flexible alternative,
Ali T. Hammad, Alexis Habineza, Ahmed M. Gemeay, Fatimah A. Almulhim   +3 more
doaj   +1 more source

Bivariate Random Coefficient Integer-Valued Autoregressive Model Based on a ρ-Thinning Operator

Axioms
While overdispersion is a common phenomenon in univariate count time series data, its exploration within bivariate contexts remains limited. To fill this gap, we propose a bivariate integer-valued autoregressive model.
Chang Liu, Dehui Wang
doaj   +1 more source

Contrasting diversity patterns of breeding Anatidae in the Northern and Southern Hemispheres

Ecology and Evolution, 2019
For sustaining ecosystem functions and services, environmental conservation strategies increasingly target to maintain the multiple facets of biodiversity, such as functional diversity (FD) and phylogenetic diversity (PD), not just taxonomic diversity ...
Qing Zeng, Julian Reid, Neil Saintilan, Matthew J. Colloff, Guangchun Lei, Li Wen   +5 more
doaj   +1 more source

Extended Poisson INAR(1) processes with equidispersion, underdispersion and overdispersion [PDF]

, 2018
Marcelo Bourguignon, Josemar Rodrigues, Manoel Santos‐Neto   +2 more
openalex   +1 more source

Information Initiatives of Mobile Retailers: A Regression Analysis of Zero-Truncated Count Data with Underdispersion [PDF]

, 2014
Yen‐Chun Chou, Howard Hao‐Chun Chuang, Benjamin B. M. Shao   +2 more
openalex   +2 more sources