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.
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Communicated by Domingo Morales.
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Li, D., Peng, L. & Qi, Y. Empirical likelihood confidence intervals for the endpoint of a distribution function. TEST 20, 353–366 (2011). https://doi.org/10.1007/s11749-010-0204-4
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DOI: https://doi.org/10.1007/s11749-010-0204-4