标题: | Symmetric quantiles and their applications |
作者: | Chiang, Yuang-Chin Chen, Lin-An Yang, Hsien-Chueh Peter 统计学研究所 Institute of Statistics |
关键字: | regression quantile;scale estimator;trimmed mean |
公开日期: | 1-九月-2006 |
摘要: | To develop estimators with stronger efficiencies than the trimmed means which use the empirical quantile, Kim (1992) and Chen & Chiang (1996), implicitly or explicitly used the symmetric quantile, and thus introduced new trimmed means for location and linear regression models, respectively. This study further investigates the properties of the symmetric quantile and extends its application in several aspects. ( a) The symmetric quantile is more efficient than the empirical quantiles in asymptotic variances when quantile percentage a is either small or large. This reveals that for any proposal involving the alpha th quantile of small or large alpha s, the symmetric quantile is the right choice; (b) a trimmed mean based on it has asymptotic variance achieving a Cramer-Rao lower bound in one heavy tail distribution; ( c) an improvement of the quantiles-based control chart by Grimshaw & Alt ( 1997) is discussed; (d) Monte Carlo simulations of two new scale estimators based on symmetric quantiles also support this new quantile. |
URI: | http://dx.doi.org/10.1080/02664760600743464 http://hdl.handle.net/11536/11892 |
ISSN: | 0266-4763 |
DOI: | 10.1080/02664760600743464 |
期刊: | JOURNAL OF APPLIED STATISTICS |
Volume: | 33 |
Issue: | 8 |
起始页: | 807 |
结束页: | 817 |
显示于类别: | Articles |
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