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Mixtures of Autoregressions with an Improper Component for Panel Data

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  • Nicholas Longford
  • Pierpaolo D’Urso

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. Copyright Springer Science+Business Media, LLC 2012

Suggested Citation

  • Nicholas Longford & Pierpaolo D’Urso, 2012. "Mixtures of Autoregressions with an Improper Component for Panel Data," Journal of Classification, Springer;The Classification Society, vol. 29(3), pages 341-362, October.
    • Handle: RePEc:spr:jclass:v:29:y:2012:i:3:p:341-362
    DOI: 10.1007/s00357-012-9111-6
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    References listed on IDEAS

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    1. Pietro Coretto & Christian Hennig, 2010. "A simulation study to compare robust clustering methods based on mixtures," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 4(2), pages 111-135, September.
    2. Longford, N.T. & Pittau, M.G., 2006. "Stability of household income in European countries in the 1990s," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1364-1383, November.
    3. N. T. Longford & Pierpaolo D'Urso, 2011. "Mixture models with an improper component," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(11), pages 2511-2521, January.
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