A smooth nonparametric quantile estimator from right-censored data |
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| Institution: | 1. School of Management, Hefei University of Technology, Hefei, 230009, China;2. Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei, 230009, China;3. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing, 100048, China;1. Center for Management & Commerce, University of Swat, Khyber Pakhtunkhwa, Pakistan;2. School of Economics and Management, Beijing University of Chemical Technology, 100029, China;3. School of Business, Wuyi University, Wuyishan, 354300, China;4. Regional Green Development Center, Wuyi University, Wuyishan, 354300, China;5. College of Tourism and Service Management, Nankai University, Tianjin, 300071, China |
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| Abstract: | Based on randomly right-censored data, a smooth nonparametric estimator of the quantile function of the lifetime distribution is studied. The estimator is defined to be the solution xn(p) of Fn(xn(p)) = p, where Fn is the distribution function corresponding to a kernel estimator of the lifetime density. The strong consistency and asymptotic normality of xn(p) are shown. Data-based selection of the bandwidth required for computing Fn is investigated using bootstrap methods. Illustrative examples are given. |
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