ℒ1-deficiency of the sample quantile estimator with respect to a kernel quantile estimator

Mu Zhao, Hongmei Jiang*, Yong Zhou

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

The performance of the sample quantile estimator versus a kernel quantile estimator under the criterion of mean integrated absolute error (MIAE) for randomly right-censored data is considered in this paper. We show that the so called ℒ1-deficiency of the sample quantile estimator with respect to the kernel quantile estimator is convergent to infinity. The optimal bandwidth in the sense of MIAE is obtained. Some simulation studies and one real data analysis are used to illustrate the results.

Original languageEnglish (US)
Pages (from-to)2399-2406
Number of pages8
JournalStatistics and Probability Letters
Volume83
Issue number10
DOIs
StatePublished - Oct 2013

Keywords

  • -deficiency
  • Kernel quantile estimator
  • Optimal bandwidth
  • Sample quantile estimator

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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