Recursive estimation of the observation and process noise covariances in online Kalman filtering

DOI10.1016/0377-2217(81)90234-4zbMath0456.93054OpenAlexW1977136274MaRDI QIDQ1150564

Derek W. Bunn

Publication date: 1981

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0377-2217(81)90234-4

zbMATH Keywords

Kalman filteringtime series analysisstatistical forecasting

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Filtering in stochastic control theory (93E11) Estimation and detection in stochastic control theory (93E10)

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Cites Work

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• On the use of Bayesian composite predictors in decision analysis
• Estimation of noise covariance matrices for a linear time-varying stochastic process
• Adaptive Filtering Revisited
• Kalman Filtering Applied to Statistical Forecasting
• Estimation of steady-state Kalman filter gain
• Identification of optimum filter steady-state gain for systems with unknown noise covariances
• Exponential Smoothing and Short-Term Sales Forecasting
• A Bayesian Approach to Short-term Forecasting
• Approaches to adaptive filtering
• Adaptive filtering

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