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.
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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.
- Confidence interval
- Coverage probability
- Empirical likelihood method