Bandingkan metode

	Model Rata-rata Bergerak (MA) Bayesian	Model Rata-rata Bergerak (MA)
Bidang	Ekonometrika	Ekonometrika
Keluarga	Regression model	Regression model
Tahun asal	1970s–1997	1970
Pencetus	Bayesian framework applied to Box-Jenkins MA models; West & Harrison (1997) canonical treatment	Box and Jenkins
Tipe	Bayesian time series model	Linear time series model
Sumber perintis	West, M., & Harrison, J. (1997). Bayesian Forecasting and Dynamic Models (2nd ed.). Springer. ISBN: 978-0387947259	Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0130607744
Alias	Bayesian MA, Bayesian moving average, BMA time series, MA model with Bayesian estimation	MA model, MA(q) process, moving-average process, Box-Jenkins MA
Terkait	6	5
Ringkasan	The 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.