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Bayesian MA model/Evidence
Method evidence record

Bayesian MA model

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.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Bayesian Moving Average Model
Taxonomic method record · regression-model / econometrics
  • West, M., & Harrison, J. (1997). Bayesian Forecasting and Dynamic Models (2nd ed.). Springer. · ISBN 978-0387947259
  • Geweke, J., & Meese, R. (1981). Estimating regression models of finite but unknown order. International Economic Review, 22(1), 55–70. · URL
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Related methods

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Taxonomic bucketARIMA modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketBayesian AR modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketBayesian ARIMA modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketBayesian ARMA modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketBayesian VAR modelmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketMoving Average Modelmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

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Sources

2 recorded citations, copied from the method source record.

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