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Modello ARIMA di Fourier×Modello ARIMA (Autoregressive Integrated Moving Average)×Modello SARIMA×
CampoEconometriaEconometriaEconometria
FamigliaRegression modelRegression modelRegression model
Anno di origine2004-201219701970 (first edition); 1976 (revised)
IdeatoreBecker, Enders, and Hurn; further extended by Enders and LeeGeorge Box and Gwilym JenkinsBox, Jenkins, and Reinsel
TipoTime series modelTime series forecasting modelSeasonal time series model
Fonte seminaleEnders, W., & Lee, J. (2012). The flexible Fourier form and Dickey-Fuller type unit root tests. Economics Letters, 117(1), 196-202. DOI ↗Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0130607744
AliasFourier ARIMA, ARIMA with Fourier terms, trigonometric ARIMA, Fourier-flexible ARIMAARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)SARIMA, seasonal ARIMA, Box-Jenkins seasonal model, ARIMA with seasonal component
Correlati265
SintesiThe Fourier ARIMA model augments a standard ARIMA specification with trigonometric sine and cosine terms, allowing it to capture smooth, gradual structural change and flexible nonlinear seasonality without specifying the exact timing or number of breaks in advance. It is widely used in applied macroeconometrics and finance for series exhibiting slowly evolving dynamics.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.SARIMA extends ARIMA by adding seasonal autoregressive and moving-average operators to capture repeating patterns at fixed intervals — such as monthly, quarterly, or annual cycles. Denoted SARIMA(p,d,q)(P,D,Q)s, it is the standard workhorse for univariate seasonal time series forecasting in econometrics, economics, and official statistics.
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ScholarGateConfronta i metodi: Fourier ARIMA model · ARIMA model · SARIMA model. Consultato il 2026-06-18 da https://scholargate.app/it/compare