مقایسهٔ روش‌ها

	مدل فوریه-ساریمـا	مدل آریما (میانگین متحرک یکپارچه خودرگرسیو)
حوزه	اقتصادسنجی	اقتصادسنجی
خانواده	Regression model	Regression model
سال پیدایش	1994	1970
پدیدآور	Harvey & Scott (1994); Hyndman & Athanasopoulos (popularization)	George Box and Gwilym Jenkins
نوع	Seasonal time series model with trigonometric regressors	Time series forecasting model
منبع بنیادین	Harvey, A., & Scott, A. (1994). Seasonality in dynamic regression models. The Economic Journal, 104(427), 1324-1345.	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.
نام‌های دیگر	Fourier SARIMA, SARIMA with Fourier terms, Fourier-SARIMA, trigonometric SARIMA	ARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)
مرتبط	6	6
خلاصه	The Fourier SARIMA model extends the classical Seasonal ARIMA framework by incorporating trigonometric (Fourier) terms as deterministic regressors. This allows the model to approximate smooth, complex, or multiple-frequency seasonal patterns without requiring a full seasonal ARIMA structure for every frequency, making it particularly useful for high-frequency data or series with non-integer or evolving seasonality.	The ARIMA(p,d,q) model is the standard workhorse for univariate time series forecasting. It combines autoregressive terms (past values), differencing to induce stationarity, and moving average terms (past shocks) into a unified linear framework. Developed by Box and Jenkins (1970), it remains one of the most widely applied models in econometrics and applied statistics.