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SARIMA-Modell×Moving Average (MA) Modell×
FachgebietÖkonometrieÖkonometrie
FamilieRegression modelRegression model
Entstehungsjahr1970 (first edition); 1976 (revised)1970
UrheberBox, Jenkins, and ReinselBox and Jenkins
TypSeasonal time series modelLinear time series model
Wegweisende QuelleBox, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0130607744Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0130607744
AliasnamenSARIMA, seasonal ARIMA, Box-Jenkins seasonal model, ARIMA with seasonal componentMA model, MA(q) process, moving-average process, Box-Jenkins MA
Verwandt55
ZusammenfassungSARIMA 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.The Moving Average model of order q — written MA(q) — expresses the current value of a time series as a linear combination of the current and past random shocks (innovations). Unlike the AR model which uses lagged values of the series itself, the MA model uses lagged error terms, making it well-suited for capturing short-lived disturbances that dissipate over q periods.
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ScholarGateMethoden vergleichen: SARIMA model · Moving Average Model. Abgerufen am 2026-06-15 von https://scholargate.app/de/compare