방법 비교

	푸리에 AR 모형	ARMA 모형 (자기회귀 이동평균)
분야	계량경제학	계량경제학
계열	Regression model	Regression model
기원 연도	2012	1970
창시자	Enders & Lee	George E. P. Box and Gwilym M. Jenkins
유형	Time series model with Fourier augmentation	Time series model
원전	Enders, W., & Lee, J. (2012). A unit root test using a Fourier series to approximate smooth breaks. Oxford Bulletin of Economics and Statistics, 74(4), 574–599.	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.
별칭	Fourier AR, trigonometric AR model, smooth transition AR with Fourier terms, FAR model	ARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)
관련	6	5
요약	The Fourier AR model extends the standard autoregressive specification by adding trigonometric (sine and cosine) terms to the deterministic component. This allows the model to capture smooth, gradual shifts in the mean or trend of a time series without requiring the researcher to locate or count structural break points explicitly.	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.