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Bayes prediction based on right censored data

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Abstract

This paper is concerned with a Bayes prediction problem in the exponential distribution under random censorship. Using censored samples, we work out a prediction interval for a sum of interest which consists of some future samples. Differing from the general Bayes approach, we do not specify the prior distribution of the parameter, and only a first moment condition on the prior is assumed. Simulation studies are conducted to exhibit the coverage probabilities of the prediction interval.

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Authors and Affiliations

  1. Department of Mathematics, Beijing Jiaotong University, Beijing, 100044, China

    Lichun Wang

  2. Center for Statistics, Universiteit Hasselt, 3590, Diepenbeek, Belgium

    Noël Veraverbeke

Authors
  1. Lichun Wang
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  2. Noël Veraverbeke
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Corresponding author

Correspondence to Noël Veraverbeke.

Additional information

Financial support from the IAP research network (#P5/24) of the Belgian Government (Belgian Science Policy) is gratefully acknowledged.

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Wang, L., Veraverbeke, N. Bayes prediction based on right censored data. Stat Papers 50, 137–149 (2009). https://doi.org/10.1007/s00362-006-0044-1

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  • DOI: https://doi.org/10.1007/s00362-006-0044-1

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