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Model ARMA (Autoregresif Moving Average)×Model Purata Bergerak (MA)×
BidangEkonometrikEkonometrik
KeluargaRegression modelRegression model
Tahun asal19701970
PengasasGeorge E. P. Box and Gwilym M. JenkinsBox and Jenkins
JenisTime series 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
AliasARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)MA model, MA(q) process, moving-average process, Box-Jenkins MA
Berkaitan55
RingkasanThe 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.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 kaedah: ARMA model · Moving Average Model. Dicapai 2026-06-15 daripada https://scholargate.app/ms/compare