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 |
| 卷 | 26 |
| 期 | 4 |
| DOI | |
| 出版状态 | 已出版 - 2006 |
| 已对外发布 | 是 |
指纹
探究 '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)' 的科研主题。它们共同构成独一无二的指纹。引用此
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