Generalized order statistics: An exponential family in model parameters

S. Bedbur*, E.A. Beutner, U. Kamps

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Generalized order statistics, and thus sequential order statistics with conditional proportional hazard rates, are shown to form a regular exponential family in the model parameters. This structure is utilized to derive maximum likelihood estimators for these parameters or functions of them along with several properties of the estimators. The Fisher information matrix is stated, and asymptotic efficiency is shown.

Original languageEnglish
Pages (from-to)159-166
Number of pages8
JournalStatistics
Volume46
Issue number2
DOIs
Publication statusPublished - 1 Jan 2012

Keywords

  • sequential order statistics
  • conditional proportional hazard rates
  • sequential k-out-of-n system
  • regular exponential family
  • maximum likelihood estimation
  • uniformly minimum variance unbiased estimation
  • Fisher information matrix
  • asymptotic efficiency
  • OF-N SYSTEMS
  • DISTRIBUTIONS
  • INFERENCE

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