Comparer des méthodes

	Modèle de prévision grise GM(1,1)	Modèle ARIMA (Autoregressive Integrated Moving Average)
Domaine	Soft computing	Économétrie
Famille	Regression model	Regression model
Année d'origine	1982	2015
Auteur d'origine	Julong Deng	Box & Jenkins (Box-Jenkins methodology)
Type	Small-sample grey forecasting model	Univariate time-series model
Source fondatrice	Deng, J. L. (1982). Control problems of grey systems. Systems & Control Letters, 1(5), 288–294.	Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021
Alias	GM(1,1), grey prediction model, grey forecasting, gri tahmin modeli	Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli
Apparentées	2	5
Résumé	GM(1,1) is the core forecasting model of grey system theory, introduced by Julong Deng in 1982, designed to predict from very few observations and incomplete information — situations where classical time-series models like ARIMA need far more data. It accumulates the raw series to expose a hidden exponential trend, fits a first-order grey differential equation, and projects future values, making it popular in engineering, energy, and management forecasting with short data records.	ARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015).