Empirical likelihood confidence intervals for the endpoint of a distribution function

Deyuan Li, Liang Peng, Yongcheng Qi

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Estimating the endpoint of a distribution function is of interest in product analysis and predicting the maximum lifetime of an item. In this paper, we propose an empirical likelihood method to construct a confidence interval for the endpoint. A simulation study shows the proposed confidence interval has better coverage accuracy than the normal approximation method, and bootstrap calibration improves the accuracy.

Original languageEnglish (US)
Pages (from-to)353-366
Number of pages14
JournalTest
Volume20
Issue number2
DOIs
StatePublished - Aug 2011

Bibliographical note

Funding Information:
Acknowledgements We thank two reviewers for helpful comments. Li’s research was partly supported by NNSFC Grant 10801038. Peng’s research was supported by NSA Grant H98230-10-1-0170 and Qi’s research was supported by NSA Grant H98230-10-1-0161.

Keywords

  • Confidence interval
  • Coverage probability
  • Empirical likelihood method
  • Endpoint

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