เปรียบเทียบวิธี

	แบบจำลองฟูเรียร์ ARMA	แบบจำลอง ARMA ไม่เชิงเส้น (NARMA)
สาขาวิชา	เศรษฐมิติ	เศรษฐมิติ
ตระกูล	Regression model	Regression model
ปีกำเนิด	2004–2006	1980s–1990s
ผู้ริเริ่ม	Becker, Enders, and Hurn	Tong (1990); Granger & Terasvirta (1993)
ประเภท	Time series model with smooth structural change	Nonlinear time series model
แหล่งต้นตำรับ	Becker, R., Enders, W., & Hurn, S. (2006). A general test for time dependence in parameters. Journal of Applied Econometrics, 21(7), 1005–1028.	Tong, H. (1990). Non-linear Time Series: A Dynamical System Approach. Oxford University Press. ISBN: 978-0198522300
ชื่อเรียกอื่น	Fourier ARMA, ARMA with Fourier terms, trigonometric ARMA, smooth structural change ARMA	NARMA, nonlinear ARMA, NLARMA, nonlinear autoregressive moving average
ที่เกี่ยวข้อง	5	2
สรุป	The Fourier ARMA model augments the classical Autoregressive Moving Average framework with low-frequency Fourier (sine and cosine) terms to capture smooth, gradual shifts in the mean or trend of a time series. Unlike dummy-variable approaches, it requires no prior knowledge of when structural change occurred, approximating change with flexible trigonometric functions.	The Nonlinear ARMA (NARMA) model extends the classical linear ARMA framework by allowing the conditional mean to depend on past observations and past errors through an arbitrary nonlinear function. It captures complex dynamics — such as regime changes, asymmetric cycles, and threshold effects — that linear models miss, making it valuable for economic and financial time series.