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Regime Signaling Techniques for Non-Stationary Time-Series Forecasting

By Radu Drossu and Zoran Obradovii

Abstract

An accuracy-based signaling technique is proposed as an alternative to a statistics-based signaling for detecting changes in a time series distribution. Three different forecasting scenarios are analyzed in order to decide whether to reuse historically successful neural network models or retrain new ones when a change in the distribution is signaled. The results obtained on low-noise and high-noise, non-stationary time series provide strong evidence in favor of the accuracy-based signaling technique.

Topics: zoranqeecs. wsii.edii
Year: 1996
OAI identifier: oai:CiteSeerX.psu:10.1.1.352.5016
Provided by: CiteSeerX
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