Journal of Advanced Statistics

Download PDF (232.2 KB) PP. 171 - 180 Pub. Date: September 1, 2016

DOI: 10.22606/jas.2016.13006

• Yijun Zuo^*
  Department of Statistics and Probability, Michigan State University, East Lansing, MI 48824, USA

Woodruff confidence interval for quantiles is a classical procedure and prevailing in practices and regarded as optimal one for many practitioners. This manuscript examines the performance of bootstrap based confidence interval and the classical Woodruff one for quantiles. It is found that the bootstrap procedure can outperform the Woodruff one in terms of coverage probability( accuracy) and the length of the intervals(efficiency). The validity of these theoretical findings for large sample is further confirmed in finite sample simulation studies.

Quantile, bootstrap, Bahadur representation, Confidence interval, Coverage probability, Length of confidence interval.

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