Random Weighting Estimation of Confidence Intervals for Quantiles
Article first published online: 11 APR 2013
© 2013 Australian Statistical Publishing Association Inc. Published by Wiley Publishing Asia Pty Ltd.
Australian & New Zealand Journal of Statistics
Volume 55, Issue 1, pages 43–53, March 2013
How to Cite
Gao, S., Zhong, Y. and Gu, C. (2013), Random Weighting Estimation of Confidence Intervals for Quantiles. Australian & New Zealand Journal of Statistics, 55: 43–53. doi: 10.1111/anzs.12018
- Issue published online: 11 APR 2013
- Article first published online: 11 APR 2013
- confidence interval;
- random weighting estimation
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.