標題: Symmetric quantiles and their applications
作者: Chiang, Yuang-Chin
Chen, Lin-An
Yang, Hsien-Chueh Peter
統計學研究所
Institute of Statistics
關鍵字: regression quantile;scale estimator;trimmed mean
公開日期: 1-Sep-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
起始頁: 807
結束頁: 817
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