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Model ARIMA (Autoregressive Integrated Moving Average)×Model Rata-rata Bergerak (MA)×
BidangEkonometrikaEkonometrika
KeluargaRegression modelRegression model
Tahun asal19701970
PencetusGeorge Box and Gwilym JenkinsBox and Jenkins
TipeTime series forecasting modelLinear time series model
Sumber perintisBox, 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
AliasARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)MA model, MA(q) process, moving-average process, Box-Jenkins MA
Terkait65
RingkasanThe 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.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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ScholarGateBandingkan metode: ARIMA model · Moving Average Model. Diakses 2026-06-15 dari https://scholargate.app/id/compare