Recursive computation of the single and product moments of order statistics from the complementary exponential–geometric distribution

N. Balakrishnan*, Xiaojun Zhu, Bander Al-Zahrani

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)

Abstract

The complementary exponential–geometric distribution has been proposed recently as a simple and useful reliability model for analysing lifetime data. For this distribution, some recurrence relations are established for the single and product moments of order statistics. These recurrence relations enable the computation of the means, variances and covariances of all order statistics for all sample sizes in a simple and efficient recursive manner. By using these relations, we have tabulated the means, variances and covariances of order statistics from samples of sizes up to 10 for various values of the shape parameter θ. These values are in turn used to determine the best linear unbiased estimator of the scale parameter β based on complete and Type-II right-censored samples.

Original languageEnglish
Pages (from-to)2187-2201
Number of pages15
JournalJournal of Statistical Computation and Simulation
Volume85
Issue number11
DOIs
Publication statusPublished - 24 Jul 2015
Externally publishedYes

Keywords

  • Type-II censoring
  • best linear unbiased estimator
  • complementary exponential–geometric distribution
  • covariances
  • means
  • order statistics
  • product moments
  • recurrence relations
  • single moments
  • variances

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