Comparer des méthodes

	Méthode de Croston pour la demande intermittente	Régression de Poisson et binomiale négative
Domaine	Économétrie	Économétrie
Famille	Regression model	Regression model
Année d'origine	1972	1998
Auteur d'origine	J. D. Croston (1972)	Cameron & Trivedi (textbook treatment); Hilbe (negative binomial)
Type	Intermittent demand time-series forecasting	Generalized linear model for count data
Source fondatrice	Croston, J. D. (1972). Forecasting and Stock Control for Intermittent Demands. Operational Research Quarterly, 23(3), 289-303.	Cameron, A. C. & Trivedi, P. K. (1998). Regression Analysis of Count Data. Cambridge University Press.
Alias	Croston method, intermittent demand forecasting, Croston Yöntemi — Aralıklı Talep Tahmini	count regression, log-linear count model, negative binomial regression, Poisson / Negatif Binom Regresyon
Apparentées	4	4
Résumé	Croston's method, introduced by J. D. Croston in 1972, is a time-series forecasting technique built for intermittent demand series in which periods of zero demand are frequent. Instead of forecasting the raw series, it models the size of demand when it occurs and the interval between demand occurrences as two separate processes.	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.