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A KERNEL-TYPE ESTIMATOR OF A QUANTILE FUNCTION UNDER RANDOMLY TRUNCATED DATA* * Zhou's research was partially supported by the NNSF of China (10471140, 10571169); Wu's research was partially supported by NNSF of China (0571170)

  • Yong Zhou*
  • , Guofu Wu
  • , Daoji Li
  • *此作品的通讯作者
  • CAS - Academy of Mathematics and System Sciences

科研成果: 期刊稿件文章同行评审

摘要

A kernel-type estimator of the quantile function Q(p) = inf {t : F(t) ≥ p}, 0 ≤ p ≤ 1, is proposed based on the kernel smoother when the data are subjected to random truncation. The Bahadur-type representations of the kernel smooth estimator are established, and from Bahadur representations the authors can show that this estimator is strongly consistent, asymptotically normal, and weakly convergent.

源语言英语
页(从-至)585-594
页数10
期刊Acta Mathematica Scientia
26
4
DOI
出版状态已出版 - 2006
已对外发布

指纹

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