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Nonparametric density estimation in presence of bias and censoring

  • Autores: Elodie Brunel, Fabienne Comte, Agathe Guilloux
  • Localización: Test: An Official Journal of the Spanish Society of Statistics and Operations Research, ISSN-e 1863-8260, ISSN 1133-0686, Vol. 18, Nº. 1, 2009, págs. 166-194
  • Idioma: inglés
  • Texto completo no disponible (Saber más ...)
  • Resumen
    • We consider projection estimator methods for the nonparametric estimation of the density of i.i.d. biased observations with a general known bias function w and under right censoring. Adaptive procedures to catch the optimal estimator among a collection by contrast penalization are investigated and proved to give efficient estimators with optimal nonparametric rates of convergence. Monte-Carlo experiments complete the study and illustrate the method.


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