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Пуассоновская регрессия и регрессия с отрицательным биномиальным распределением×Модель с фиксированными эффектами для панельных данных×
ОбластьЭконометрикаЭконометрика
СемействоRegression modelRegression model
Год появления19982014
Автор методаCameron & Trivedi (textbook treatment); Hilbe (negative binomial)Hsiao (textbook treatment); within transformation of panel data
ТипGeneralized linear model for count dataPanel data regression
Основополагающий источникCameron, A. C. & Trivedi, P. K. (1998). Regression Analysis of Count Data. Cambridge University Press. DOI ↗Hsiao, C. (2014). Analysis of Panel Data (3rd ed.). Cambridge University Press. DOI ↗
Другие названияcount regression, log-linear count model, negative binomial regression, Poisson / Negatif Binom Regresyonfixed effects model, within estimator, panel fixed-effects regression, Panel Veri — Sabit Etkiler Modeli
Связанные45
СводкаPoisson 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.The Panel Data Fixed Effects model estimates relationships from panel data (the same units observed over several time periods) while controlling for unit- and/or time-specific effects, supporting causal inference. It is developed as the within estimator in standard treatments such as Hsiao's Analysis of Panel Data (2014).
ScholarGateНабор данных
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  2. 2 Источники
  3. PUBLISHED
  1. v1
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ScholarGateСравнение методов: Poisson Regression · Panel Fixed Effects. Получено 2026-06-17 из https://scholargate.app/ru/compare