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Strong consistency properties of nonparametric estimators for randomly censored data, II: Estimation of density and failure rate

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Abstract

This article is Part II of a two-part study. Properties of the product-limit estimator established in the previous part [2] are now used to prove the strong consistency of some nonparametric density and failure rate estimators which can be used with randomly censored data.

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Authors and Affiliations

  1. MTA Matematikai Kutató Intézet, Reáltanoda U. 13-15, H-1053, Budapest, Hungary

    A. Földes & L. Rejtő

  2. Department of Mathematics, University of Ottawa, K1N 9B4, Ottawa, Ontario, Canada

    B. B. Winter

Authors
  1. A. Földes
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  2. L. Rejtő
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  3. B. B. Winter
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Additional information

The third author's research was partly supported by the National Research Council of Canada.

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Földes, A., Rejtő, L. & Winter, B.B. Strong consistency properties of nonparametric estimators for randomly censored data, II: Estimation of density and failure rate. Period Math Hung 12, 15–29 (1981). https://doi.org/10.1007/BF01848168

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  • DOI: https://doi.org/10.1007/BF01848168

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