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Bootstrap for the conditional distribution function with truncated and censored data

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Abstract

We propose a resampling method for left truncated and right censored data with covariables to obtain a bootstrap version of the conditional distribution function estimator. We derive an almost sure representation for this bootstrapped estimator and, as a consequence, the consistency of the bootstrap is obtained. This bootstrap approximation represents an alternative to the normal asymptotic distribution and avoids the estimation of the complicated mean and variance parameters of the latter.

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Authors and Affiliations

  1. Department de Estadística e Investigación Operativa, Escuela Universitaria de Ingeniería Técnica Forestal, Universidad de Vigo, Gampus de Pontevedra, 36005, Pontevedra, Spain

    M. C. Iglesias Pérez

  2. Departamento de Estadística e Investigación Operativa, Facultad de Matemáticas, Universidad de Santiago de Compostela, Campus Sur, Santiago de Compostela, 15706, Spain

    W. González Manteiga

Authors
  1. M. C. Iglesias Pérez
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  2. W. González Manteiga
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Iglesias Pérez, M.C., González Manteiga, W. Bootstrap for the conditional distribution function with truncated and censored data. Ann Inst Stat Math 55, 331–357 (2003). https://doi.org/10.1007/BF02530503

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  • DOI: https://doi.org/10.1007/BF02530503

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