Nonparametric sequential prediction of time series

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Time series prediction covers a vast field of every-day 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 normalized cumulative prediction error.
article + 2 figures

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Methodology, Probability, 62G99

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http://salesiana.dossiersoluciones.com/handle/123456789/145166

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/0801.0327
 http://arxiv.org/abs/0801.0327

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arXiv