Calibrated interpolated confidence intervals for population quantiles
成果类型：
Article
署名作者：
Ho, YHS; Lee, SMS
署名单位：
University of Hong Kong
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.1093/biomet/92.1.234
发表日期：
2005
页码：
234241
关键词：
摘要：
Beran & Hall's (1993) simple linear interpolation provides a very convenient approach for constructing nonparametric confidence intervals for population quantiles based on a random sample of size n. We show that the coverage error of the interpolated interval, which is of order O(n(-1)), can be improved upon by calibrating the nominal coverage level. Three distinct methods of calibration are considered. The analytical and Monte Carlo methods succeed in reducing the order of coverage error to O(n(-3/2)), while the smoothed bootstrap method reduces it further to O(n(-25/14)). We provide guidelines for practical implementation of the calibration methods. Their performance is compared with the simple linear interpolated interval in a simulation study which confirms superiority of the calibrated intervals.