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Mixtures of Autoregressions with an Improper Component for Panel Data

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Abstract

An EM algorithm for fitting mixtures of autoregressions of low order is constructed and the properties of the estimators are explored on simulated and real datasets. The mixture model incorporates a component with an improper density, which is intended for outliers. The model is proposed as an alternative to the search for the order of a single-component autoregression. The methods can be adapted to other patterns of dependence in panel data. An application to the monthly records of income of the outlets of a retail company is presented.

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Authors and Affiliations

  1. Departament d’Economia i Empresa, SNTL and University Pompeu Fabra, Ramon Trias Fargas 25-27, 08005, Barcelona, Spain

    Nicholas T. Longford

  2. Sapienza University, Rome, Italy

    Pierpaolo D’Urso

Authors
  1. Nicholas T. Longford
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  2. Pierpaolo D’Urso
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Corresponding author

Correspondence to Nicholas T. Longford.

Additional information

Partial support by the Grant SEJ–2006–13537 from the Spanish Ministry of Science and Technology and the Grant GAČR 402/09/0515 from the Science Foundation of the Czech Republic is acknowledged. The data were obtained from a source that wishes its identity not to be disclosed. Helpful comments and suggestions of Aleix Ruiz de Villa Robert and three anonymous referees are acknowledged.

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Longford, N.T., D’Urso, P. Mixtures of Autoregressions with an Improper Component for Panel Data. J Classif 29, 341–362 (2012). https://doi.org/10.1007/s00357-012-9111-6

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  • DOI: https://doi.org/10.1007/s00357-012-9111-6

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