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Relative deficiency of quantile estimators for left truncated and right censored data
Authors:Mu Zhao  Fangfang Bai  Yong Zhou
Affiliation:
  • a Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China
  • b School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai 200433, China
  • c School of Mathematical Sciences, Anhui University, Hefei 230039, China
  • Abstract:The quantity deficiency which was proposed by Hodges and Lehmann (1970) is used to compare different statistical procedures. In this article, the deficiency of the sample quantile estimator with respect to the kernel quantile estimator for left truncated and right censored (LTRC) data in the sense of Hodges and Lehmann is considered. We also give the optimal bandwidth for the kernel quantile estimator. Monte Carlo studies are conducted to illustrate our results.
    Keywords:Truncated and censored data   Quantile estimator   Smoothed quantile estimator   Deficiency
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