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Bootstrapping pairs in Distance-Based Regression

Author

Listed:
  • Eva Boj del Val
  • M. Mercedes Claramunt Bielsa
  • Jose Fortiana Gregori

    (Universitat de Barcelona)

Abstract

Distance-based regression is a prediction method consisting of two steps: from distances between observations we obtain latent variables which, in turn, are the regressors in an ordinary least squares linear model. Distances are computed from actually observed predictors by means of a suitable dissimilarity function. Being in general nonlinearly related with the response their selection by the usual F tests is unavailable. In this paper we propose a solution to this predictor selection problem, by defining generalized test statistics and adapting a non-parametric bootstrap method to estimate their p-values. We include a numerical example with automobile insurance data.

Suggested Citation

  • Eva Boj del Val & M. Mercedes Claramunt Bielsa & Jose Fortiana Gregori, 2006. "Bootstrapping pairs in Distance-Based Regression," Working Papers in Economics 154, Universitat de Barcelona. Espai de Recerca en Economia.
  • Handle: RePEc:bar:bedcje:2006154
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    File URL: http://www.ere.ub.es/dtreball/E06154.rdf/at_download/file
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    References listed on IDEAS

    as
    1. Flachaire, Emmanuel, 1999. "A better way to bootstrap pairs," Economics Letters, Elsevier, vol. 64(3), pages 257-262, September.
    2. J. Gower & P. Legendre, 1986. "Metric and Euclidean properties of dissimilarity coefficients," Journal of Classification, Springer;The Classification Society, vol. 3(1), pages 5-48, March.
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    More about this item

    JEL classification:

    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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