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Zero-Inflateret Poisson (ZIP) Regression×Logistisk regression×
FagområdeStatistikForskningsstatistik
FamilieRegression modelProcess / pipeline
Oprindelsesår19921958
OphavspersonDiane LambertDavid Roxbee Cox
TypeCount regression (two-component mixture)Method
Oprindelig kildeLambert, D. (1992). Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing. Technometrics, 34(1), 1–14. DOI ↗Cox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗
AliasserZIP regression, zero-inflated count model, Sıfır-Şişirilmiş Poisson Regresyonu (ZIP)logit model, binomial logistic regression, LR
Relaterede43
ResuméZero-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.Logistic regression is a statistical method for modeling the probability of a binary outcome (disease present/absent, success/failure) as a function of continuous and categorical predictors. Developed by David Roxbee Cox (1958), it solves the problem of predicting categorical outcomes by applying a logistic transformation to constrain predictions to the [0,1] probability interval, enabling accurate risk stratification, diagnostic prediction, and causal inference in epidemiology, medicine, and social science.
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ScholarGateSammenlign metoder: Zero-Inflated Poisson Regression · Logistic Regression. Hentet 2026-06-18 fra https://scholargate.app/da/compare