A strong representation of the product-limit estimator for left truncated and right censored data
文献类型：期刊论文
| 作者 | Zhou, Y ; Yip, PSF
|
| 刊名 | JOURNAL OF MULTIVARIATE ANALYSIS
 |
| 出版日期 | 1999-05-01 |
| 卷号 | 69期号:2页码:261-280 |
| 关键词 | truncated data censored data product-limit estimator almost sure representation |
| ISSN号 | 0047-259X |
| 英文摘要 | In this paper we consider the TJW product-limit estimator (F) over cap(n)(x) of an unknown distribution function F when the data are subject to random left truncation and right censorship. An almost sure representation of PL-estimator (F) over cap(n)(x) is derived with an improved error bound under some weaker assumptions. We obtain the strong approximation of (F) over cap(n)(x) - F(x) by Gaussian processes and the functional law of the iterated logarithm is proved for maximal derivation of the product-limit estimator to F. A sharp rate of convergence theorem concerning the smoothed TJW product-limit estimator is obtained. Asymptotic properties of kernel estimators of density function based on TJW product-limit estimator is given. (C) 1999 Academic Press. AMS 1991 subject classifications: 62G05, 60F17, 62E20, 62G20. |
| WOS研究方向 | Mathematics |
| 语种 | 英语 |
| WOS记录号 | WOS:000080242200007 |
| 出版者 | ACADEMIC PRESS INC |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/14852]  |
| 专题 | 应用数学研究所 |
| 通讯作者 | Zhou, Y |
| 作者单位 | 1.Acad Sinica, Inst Appl Math, Beijing 100080, Peoples R China 2.Univ Hong Kong, Dept Stat, Hong Kong, Hong Kong |
| 推荐引用方式 GB/T 7714 | Zhou, Y,Yip, PSF. A strong representation of the product-limit estimator for left truncated and right censored data[J]. JOURNAL OF MULTIVARIATE ANALYSIS,1999,69(2):261-280. |
| APA | Zhou, Y,&Yip, PSF.(1999).A strong representation of the product-limit estimator for left truncated and right censored data.JOURNAL OF MULTIVARIATE ANALYSIS,69(2),261-280. |
| MLA | Zhou, Y,et al."A strong representation of the product-limit estimator for left truncated and right censored data".JOURNAL OF MULTIVARIATE ANALYSIS 69.2(1999):261-280. |
入库方式： OAI收割
来源：数学与系统科学研究院
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