Bayesian prediction of unobserved values for Type-II censored data

Tatsuya Kubota, Takeshi Kurosawa

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

In this paper, we consider posterior predictive distributions of Type-II censored data for an inverse Weibull distribution. These functions are given by using conditional density functions and conditional survival functions. Although the conditional survival functions were expressed by integral forms in previous studies, we derive the conditional survival functions in closed forms and thereby reduce the computation cost. In addition, we calculate the predictive confidence intervals of unobserved values and coverage probabilities of unobserved values by using the posterior predictive survival functions.

Original languageEnglish
Pages (from-to)1165-1180
Number of pages16
JournalJournal of Applied Statistics
Volume44
Issue number7
DOIs
Publication statusPublished - 19 May 2017

Keywords

  • Bayesian inference
  • importance sampling method
  • inverse Weibull distribution
  • log concave density function
  • posterior predictive distribution
  • Type-II censored data

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