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SETAR model selection-A bootstrap approach

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Summary

The aim of this paper is to propose new selection criteria for the orders of selfexciting threshold autoregressive (SETAR) models. These criteria use bootstrap methodology; they are based on a weighted mean of the apparent error rate in the sample and the average error rate obtained from bootstrap samples not containing the point being predicted. These new criteria are compared with the traditional ones based on the Akaike information criterion (AIC). A simulation study and an example on a real data set end the paper.

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Authors and Affiliations

  1. Department of Medical Epidemiology and Biostatistics, Karolinska Institute, P.O. Box 281, SE-17177, Stockholm, Sweden

    John Öhrvik

  2. Dipartimento di Scienze Economiche e Statistiche, Universitá di Trieste, Piazzale Europa 1, IT-34127, Trieste, Italy

    Gabriella Schoier

Authors
  1. John Öhrvik
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  2. Gabriella Schoier
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Öhrvik, J., Schoier, G. SETAR model selection-A bootstrap approach. Computational Statistics 20, 559–573 (2005). https://doi.org/10.1007/BF02741315

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  • DOI: https://doi.org/10.1007/BF02741315

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