เปรียบเทียบวิธี

	แบบจำลอง ARMA (Autoregressive Moving Average)	แบบจำลอง ARDL ไม่เชิงเส้น (NARDL)
สาขาวิชา	เศรษฐมิติ	เศรษฐมิติ
ตระกูล	Regression model	Regression model
ปีกำเนิด	1970	2014
ผู้ริเริ่ม	George E. P. Box and Gwilym M. Jenkins	Shin, Yu & Greenwood-Nimmo
ประเภท	Time series model	Nonlinear cointegration model
แหล่งต้นตำรับ	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.	Shin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In R. C. Sickles & W. C. Horrace (Eds.), Festschrift in Honor of Peter Schmidt: Econometric Methods and Applications (pp. 281–314). Springer.
ชื่อเรียกอื่น	ARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)	NARDL, nonlinear bounds test, asymmetric ARDL, asymmetric cointegration model
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 Nonlinear ARDL (NARDL) model extends the linear ARDL bounds-testing framework to allow asymmetric long-run and short-run relationships. By decomposing the regressor into cumulative positive and negative partial sums, it tests whether increases and decreases in a variable exert different effects on the outcome — a feature especially relevant in financial and energy economics where positive and negative shocks rarely cancel out symmetrically.