Random Weighting Estimation of Confidence Intervals for Quantiles |
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| Authors: | Shesheng Gao Yongmin Zhong Chengfan Gu |
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| Institution: | 1. School of Automatics, Northwestern Polytechnical University, Xi'an, Shaanxi, , China, 710072;2. School of Aerospace, Mechanical and Manufacturing Engineering, RMIT University, , PO Box 71 Bundoora, VIC, 3083 Australia;3. School of Materials Science and Engineering, The University of New South Wales, , Sydney, NSW 2052 Australia |
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| Abstract: | This paper presents a new random weighting method for confidence interval estimation for the sample  ‐quantile. A theory is established to extend ordinary random weighting estimation from a non‐smoothed function to a smoothed function, such as a kernel function. Based on this theory, a confidence interval is derived using the concept of backward critical points. The resultant confidence interval has the same length as that derived by ordinary random weighting estimation, but is distribution‐free, and thus it is much more suitable for practical applications. Simulation results demonstrate that the proposed random weighting method has higher accuracy than the Bootstrap method for confidence interval estimation. |
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| Keywords: | confidence interval q‐quantile random weighting estimation |
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