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Poisson-regresjon med nullinflasjon (ZIP)×Poisson- og negativ binomial regresjon×
FagfeltStatistikkØkonometri
FamilieRegression modelRegression model
Opprinnelsesår19921998
OpphavspersonDiane LambertCameron & Trivedi (textbook treatment); Hilbe (negative binomial)
TypeCount regression (two-component mixture)Generalized linear model for count data
Opprinnelig kildeLambert, D. (1992). Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing. Technometrics, 34(1), 1–14. DOI ↗Cameron, A. C. & Trivedi, P. K. (1998). Regression Analysis of Count Data. Cambridge University Press. DOI ↗
AliasZIP regression, zero-inflated count model, Sıfır-Şişirilmiş Poisson Regresyonu (ZIP)count regression, log-linear count model, negative binomial regression, Poisson / Negatif Binom Regresyon
Relaterte44
SammendragZero-Inflated Poisson regression is a two-component model for count data that contains more zeros than an ordinary Poisson model can explain. Introduced by Diane Lambert in 1992, it combines a logistic model for the zero-generating mechanism with a Poisson model for the genuine counting process.Poisson regression is a generalized linear model for count outcomes — events tallied as non-negative integers such as hospital admissions, accidents, or article counts. It models the log of the expected count as a linear function of the predictors, and is developed in the standard count-data treatment of Cameron and Trivedi (1998); when the counts are over-dispersed, the closely related negative binomial model (Hilbe, 2011) is preferred.
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ScholarGateSammenlign metoder: Zero-Inflated Poisson Regression · Poisson Regression. Hentet 2026-06-18 fra https://scholargate.app/no/compare