Prediction after a Horizon of Predictability: Nonpredictable Points and Partial Multistep Prediction for Chaotic Time Series
Vasilii A. Gromov,
Philip S. Baranov
Abstract:This paper introduces several novel strategies for multi-step-ahead prediction of chaotic time series. Introducing a concept of “generalized z-vectors” (vectors of nonsuccessive time series observations) makes it possible to generate sets of possible prediction values for each point we are trying to predict. Through examining these sets, unified predictions are calculated, which are in turn used as a basis for predicting subsequent points. The key difference between the strategy presented in this paper and its… Show more
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