Uporedite metode

	Model pokretnog proseka sa Furijeovim komponentama (Fourier MA) Model	ARIMA model (Autoregresivni integrisani model pokretnih proseka)
Oblast	Ekonometrija	Ekonometrija
Porodica	Regression model	Regression model
Godina nastanka	1990s–2000s	1970
Tvorac	Harvey, A. C.; Hyndman, R. J.	George Box and Gwilym Jenkins
Tip	Time series model	Time series forecasting model
Temeljni izvor	Hyndman, R. J., & Athanasopoulos, G. (2021). Forecasting: Principles and Practice (3rd ed.). OTexts.	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.
Drugi nazivi	Fourier MA, Fourier-augmented moving average, trigonometric MA model, harmonic moving average model	ARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)
Srodne	2	6
Sažetak	The Fourier MA model combines a Moving Average (MA) error structure with Fourier series terms — sine and cosine pairs — to capture complex or high-frequency seasonal patterns in time series data. It is particularly useful when the seasonal period is long or irregular, making classical seasonal ARIMA parameterisation infeasible.	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.