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Model Purata Bergerak Bayesian (MA)×Model Purata Bergerak (MA)×
BidangEkonometrikEkonometrik
KeluargaRegression modelRegression model
Tahun asal1970s–19971970
PengasasBayesian framework applied to Box-Jenkins MA models; West & Harrison (1997) canonical treatmentBox and Jenkins
JenisBayesian time series modelLinear time series model
Sumber perintisWest, M., & Harrison, J. (1997). Bayesian Forecasting and Dynamic Models (2nd ed.). Springer. ISBN: 978-0387947259Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0130607744
AliasBayesian MA, Bayesian moving average, BMA time series, MA model with Bayesian estimationMA model, MA(q) process, moving-average process, Box-Jenkins MA
Berkaitan65
RingkasanThe Bayesian MA model estimates a moving average time series model within a fully Bayesian framework, placing prior distributions on the MA parameters and error variance and updating them via Bayes' theorem. This approach yields full posterior distributions over model parameters and produces probabilistic forecasts with coherent uncertainty quantification.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: Bayesian MA model · Moving Average Model. Dicapai 2026-06-15 daripada https://scholargate.app/ms/compare