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Modelis ar pārmērīgu nulles vērtību skaitu×Vispārīgais lineārais modelis (GLM)×
NozareStatistikaStatistika
SaimeRegression modelRegression model
Izcelsmes gads19921972
AutorsDiane LambertJohn A. Nelder & Robert W. M. Wedderburn
TipsCount regression with excess zerosRegression framework
PirmavotsLambert, D. (1992). Zero-inflated Poisson regression, with an application to defects in manufacturing. Technometrics, 34(1), 1–14. DOI ↗Nelder, J. A., & Wedderburn, R. W. M. (1972). Generalized linear models. Journal of the Royal Statistical Society: Series A (General), 135(3), 370–384. DOI ↗
Citi nosaukumiZIP model, ZINB model, zero-inflated Poisson, zero-inflated negative binomialGLM, generalized regression, exponential family regression, link-function model
Saistītās66
KopsavilkumsA zero-inflated model is a two-component mixture regression designed for count outcomes that contain more zero values than a standard Poisson or negative binomial distribution can accommodate. One component is a binary process that generates structural zeros; the other is a count process that generates both zeros and positive counts.The Generalized Linear Model is a unified regression framework that extends ordinary linear regression to outcomes from the exponential family — including binary, count, proportion, and continuous positive outcomes. A link function connects the linear predictor to the mean of the response, enabling principled modelling beyond the Gaussian case.
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ScholarGateSalīdzināt metodes: Zero-inflated model · Generalized Linear Model. Izgūts 2026-06-15 no https://scholargate.app/lv/compare