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Model selection by LASSO methods in a change-point model

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An Erratum to this article was published on 20 April 2014

Abstract

The paper considers a linear regression model with multiple change-points occurring at unknown times. The LASSO technique is very interesting since it allows simultaneously the parametric estimation, including the change-points estimation, and the automatic variable selection. The asymptotic properties of the LASSO-type (which has as particular case the LASSO estimator) and of the adaptive LASSO estimators are studied. For this last estimator the Oracle properties are proved. In both cases, a model selection criterion is proposed. Numerical examples are provided showing the performances of the adaptive LASSO estimator compared to the least squares estimator.

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Authors and Affiliations

  1. Institut Camille Jordan, Université de Lyon, Université Lyon 1, CNRS, UMR 5208, Bat. Braconnier, 43, Blvd du 11 novembre 1918, 69622, Villeurbanne Cedex, France

    Gabriela Ciuperca

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  1. Gabriela Ciuperca
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Correspondence to Gabriela Ciuperca.

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Ciuperca, G. Model selection by LASSO methods in a change-point model. Stat Papers 55, 349–374 (2014). https://doi.org/10.1007/s00362-012-0482-x

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  • DOI: https://doi.org/10.1007/s00362-012-0482-x

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