Empirical likelihood confidence intervals for the endpoint of a distribution function

Deyuan Li; Liang Peng; Yongcheng Qi

doi:10.1007/s11749-010-0204-4

Empirical likelihood confidence intervals for the endpoint of a distribution function

Deyuan Li
, Liang Peng
, Yongcheng Qi

Mathematics & Statistics

Research output: Contribution to journal › Article › peer-review

11 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 language	English (US)
Pages (from-to)	353-366
Number of pages	14
Journal	Test
Volume	20
Issue number	2
DOIs	https://doi.org/10.1007/s11749-010-0204-4
State	Published - 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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10.1007/s11749-010-0204-4

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title = "Empirical likelihood confidence intervals for the endpoint of a distribution function",

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.",

keywords = "Confidence interval, Coverage probability, Empirical likelihood method, Endpoint",

author = "Deyuan Li and Liang Peng and Yongcheng Qi",

note = "Funding Information: Acknowledgements We thank two reviewers for helpful comments. Li{\textquoteright}s research was partly supported by NNSFC Grant 10801038. Peng{\textquoteright}s research was supported by NSA Grant H98230-10-1-0170 and Qi{\textquoteright}s research was supported by NSA Grant H98230-10-1-0161.",

year = "2011",

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language = "English (US)",

volume = "20",

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T1 - Empirical likelihood confidence intervals for the endpoint of a distribution function

AU - Li, Deyuan

AU - Peng, Liang

AU - Qi, Yongcheng

N1 - 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.

PY - 2011/8

Y1 - 2011/8

N2 - 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.

AB - 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.

KW - Confidence interval

KW - Coverage probability

KW - Empirical likelihood method

KW - Endpoint

UR - https://www.scopus.com/pages/publications/80052674743

UR - https://www.scopus.com/pages/publications/80052674743#tab=citedBy

U2 - 10.1007/s11749-010-0204-4

DO - 10.1007/s11749-010-0204-4

M3 - Article

AN - SCOPUS:80052674743

SN - 1133-0686

VL - 20

SP - 353

EP - 366

JO - Test

JF - Test

IS - 2

ER -

Empirical likelihood confidence intervals for the endpoint of a distribution function

Abstract

Bibliographical note

Keywords

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