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Model ARMA (Autoregresyjny Model Średniej Ruchomej)×Model SARIMA×
DziedzinaEkonometriaEkonometria
RodzinaRegression modelRegression model
Rok powstania19701970 (first edition); 1976 (revised)
TwórcaGeorge E. P. Box and Gwilym M. JenkinsBox, Jenkins, and Reinsel
TypTime series modelSeasonal time series model
Źródło pierwotneBox, 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
Inne nazwyARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)SARIMA, seasonal ARIMA, Box-Jenkins seasonal model, ARIMA with seasonal component
Pokrewne55
PodsumowanieThe 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.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.
ScholarGateZbiór danych
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ScholarGatePorównaj metody: ARMA model · SARIMA model. Pobrano 2026-06-15 z https://scholargate.app/pl/compare