Exact smoothing for stationary and non-stationary time series

Exact smoothing for stationary and non-stationary time series

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Article ID: iaor200139
Country: Netherlands
Volume: 16
Issue: 1
Start Page Number: 59
End Page Number: 69
Publication Date: Jan 2000
Journal: International Journal of Forecasting
Authors: , ,
Keywords: Kalman filter
Abstract:

In this work we derive an analytical relationship between exact fixed-interval smoothed moments and those obtained from an arbitrarily initialized smoother. Combining this result with a conventional smoother we obtain an exact algorithm that can be applied to stationary, non-stationary or partially non-stationary systems. Other advantages of our method are its computational efficiency and numerical stability. Its extension to forecasting, filtering, fixed-point and fixed-lag smoothing is immediate, as it only requires modification of a conditioning information set. Three examples illustrate the adverse effect of an inadequate initialization on smoothed estimates.

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