เปรียบเทียบวิธี

	แบบจำลอง ARMA (Autoregressive Moving Average)	การทดสอบสาเหตุแบบแกรนเจอร์ (Granger Causality Test)
สาขาวิชา	เศรษฐมิติ	เศรษฐมิติ
ตระกูล	Regression model	Regression model
ปีกำเนิด	1970	1969
ผู้ริเริ่ม	George E. P. Box and Gwilym M. Jenkins	Clive W. J. Granger
ประเภท	Time series model	Causality test (F-test on VAR)
แหล่งต้นตำรับ	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.	Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424–438.
ชื่อเรียกอื่น	ARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)	Granger test, GC test, predictive causality test, Granger non-causality test
ที่เกี่ยวข้อง	5	5
สรุป	The ARMA(p,q) model describes a stationary time series as a combination of two components: an autoregressive part that regresses the current value on its own past p values, and a moving average part that accounts for past q error terms. It is the foundational framework of the Box-Jenkins methodology for univariate time series modelling and short-run forecasting.	The Granger causality test is a statistical hypothesis test that determines whether past values of one time series help predict future values of another, beyond what that series' own past already explains. Introduced by Clive Granger in 1969, it is the standard approach for assessing predictive causality in VAR-based time-series analysis.