विधियों की तुलना करें

	जीएम(1,1) ग्रे पूर्वानुमान मॉडल	ऑटोरेग्रेसिव इंटीग्रेटेड मूविंग एवरेज (ARIMA) मॉडल
क्षेत्र	सॉफ्ट कंप्यूटिंग	अर्थमिति
परिवार	Regression model	Regression model
उद्भव वर्ष	1982	2015
प्रवर्तक	Julong Deng	Box & Jenkins (Box-Jenkins methodology)
प्रकार	Small-sample grey forecasting model	Univariate time-series model
मौलिक स्रोत	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
उपनाम	GM(1,1), grey prediction model, grey forecasting, gri tahmin modeli	Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli
संबंधित	2	5
सारांश	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).