Nonparametric sequential prediction of time series

Gérard Biau, Kevin Bleakley, László Györfi and György Ottucsák

Journal of Nonparametric Statistics, 2010, vol. 22, issue 3, 297-317

Abstract: Time series prediction covers a vast field of everyday statistical applications in medical, environmental and economic domains. In this paper, we develop nonparametric prediction strategies based on the combination of a set of ‘experts’ and show the universal consistency of these strategies under a minimum of conditions. We perform an in-depth analysis of real-world data sets and show that these nonparametric strategies are more flexible, faster and generally outperform ARMA methods in terms of normalised cumulative prediction error.

Date: 2010
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DOI: 10.1080/10485250802680730

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