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رگرسیون پواسون با تورم صفر (ZIP)×رگرسیون لجستیک×
حوزهآمارآمار پژوهش
خانوادهRegression modelProcess / pipeline
سال پیدایش19921958
پدیدآورDiane LambertDavid Roxbee Cox
نوعCount regression (two-component mixture)Method
منبع بنیادینLambert, 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 ↗
نام‌های دیگرZIP regression, zero-inflated count model, Sıfır-Şişirilmiş Poisson Regresyonu (ZIP)logit model, binomial logistic regression, LR
مرتبط43
خلاصهZero-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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ScholarGateمقایسهٔ روش‌ها: Zero-Inflated Poisson Regression · Logistic Regression. بازیابی‌شده در 2026-06-18 از https://scholargate.app/fa/compare