Time series prediction based on data compression methods


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We propose efficient (“fast” and low memory consuming) algorithms for universal-coding-based prediction methods for real-valued time series. Previously, for such methods it was only proved that the prediction error is asymptotically minimal, and implementation complexity issues have not been considered at all. The provided experimental results demonstrate high precision of the proposed methods.

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A. Lysyak

Novosibirsk State University

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Email: accemt@gmail.com
俄罗斯联邦, Novosibirsk

B. Ryabko

Novosibirsk State University; Institute of Computational Technologies, Siberian Branch of the

Email: accemt@gmail.com
俄罗斯联邦, Novosibirsk; Novosibirsk

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