Econometric Theory · 2008 · 54 citations · 26 references
ComputingElectrical EngineeringMathematicsForecastingPredictive AnalyticsTime Series AnalysisDigital Signal ProcessingSignal ProcessingState-space ModelsStationarity AnalysisTime Series ForecastingTime Series ModelingArima ModelsAutoregressive Integrated Moving AverageFilteringFiltersMinimum Mean Square Error EstimationMoving Average ProcessesNonstationary Signal AnalysisNonstationary Time Series Analysis
The paper provides general matrix formulas for minimum mean squared error signal extraction for a finitely sampled time series whose signal and noise components are nonstationary autoregressive integrated moving average processes. These formulas are quite practical; in addition to being simple to implement on a computer, they make it possible to easily derive important general properties of the signal extraction filters. We also extend these formulas to estimates of future values of the unobserved signal, and we show how this result combines signal extraction and forecasting.
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Time Series: Theory and Methods
Eric R. Ziegel, Peter J. Brockwell, Richard A. Davis · Technometrics · 1992 · 5.1K citations
Forecasting, Structural Time Series Models and the Kalman Filter
Robert Fildes, Andrew Harvey, Mike West et al. · Journal of the Operational Research Society · 1991 · 4.8K citations
Computing, Mathematics, Forecasting +13
Time Series Analysis by State Space Methods
J. Durbin, Siem Jan Koopman · Oxford University Press eBooks · 2012 · 1.5K citations