Módszerek összehasonlítása

	GM(1,1) szürke prognosztikai modell	ARIMA (Autoregressive Integrated Moving Average) modell
Tudományterület	Lágy számítási módszerek	Ökonometria
Módszercsalád	Regression model	Regression model
Keletkezés éve	1982	2015
Megalkotó	Julong Deng	Box & Jenkins (Box-Jenkins methodology)
Típus	Small-sample grey forecasting model	Univariate time-series model
Alapmű	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
Alternatív nevek	GM(1,1), grey prediction model, grey forecasting, gri tahmin modeli	Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli
Kapcsolódó	2	5
Összefoglaló	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).