Exact predictive likelihood inference for Laplace distribution based on a time-constrained experiment

Xiaojun Zhu*, Narayanaswamy Balakrishnan, Yiliang Zhou, Hon Yiu So

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

In this paper, we will first derive explicit expressions for the predictive maximum likelihood estimators (PMLEs) for Laplace distribution based on a time-constrained life-testing experiment. Next, we derive the exact conditional distribution of the likelihood predictor of the s-th failure through the use of exact conditional moment generating function (MGF). We develop three different exact prediction intervals for the future failure, and a Monte Carlo simulation study is then carried out to check the accuracy of the derived exact inference. Finally, an example is presented to illustrate all the inferential results developed here.

Original languageEnglish
Pages (from-to)647-668
Number of pages22
JournalCommunications in Statistics: Simulation and Computation
Volume49
Issue number3
DOIs
Publication statusPublished - 3 Mar 2020

Keywords

  • Conditional moment generating function
  • Laplace distribution
  • Prediction interval
  • Predictive maximum likelihood estimators
  • Type-I censoring

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