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The strong law of large numbers for pairwise NQD random variables
  • ISSN号：1009-6124
  • 期刊名称：Journal of Systems Science and Complexity
  • 时间：2011.4.4
  • 页码：347-357
  • 分类：O212.1[理学—概率论与数理统计;理学—数学] TQ051.72[化学工程]
  • 作者机构：[1]College of Science, Guilin University of Technology, Guilin 541004, China
  • 相关基金：This research is supported by the National Natural Science Foundation of China under Grant No. 11061012, the Support Program of the New Century Guangxi China Ten-hundred-thousand Talents Project under Grant No. 2005214, and the Guangxi, China Science Foundation under Grant No. 0991081.
  • 相关项目：线性和部分线性模型的M估计研究
作者： Wu, Qunying（吴群英）|Jiang, Yuanying（蒋远营）|
关键词： 线性模型, 随机样本, 混合, 强相合, M估计, 强一致性, 参数估计, 随机错误, Linear model, M estimator, moment condition, ρ-mixing random error, strong consistency
中文摘要：

在线性模型为的回归参数的 M 评估者的强壮的一致性[(r)\tilde ] 在一些温和条件下面的 \tilde 混合 ho 随机错误被建立，它是在在片刻条件和混合错误上的文学的相关结果上的必要改进。特别，吴(2005 ) 的定理在片刻条件上实质上被改进。

英文摘要：

The strong consistency of M estimators of the regression parameters in linear models for ρ-mixing random errors under some mild conditions is established, which is an essential improvement over the relevant results in the literature on the moment conditions and mixing errors. Especially, Theorem of Wu （2005） is improved essentially on the moment conditions.

同期刊论文项目
线性和部分线性模型的M估计研究
期刊论文 62
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期刊信息
  • 《系统科学与复杂性学报：英文版》
  • 主管单位:中国科学院
  • 主办单位:中国科学院系统科学研究所
  • 主编：
  • 地址：北京东黄城根北街16号
  • 邮编：100080
  • 邮箱：
  • 电话：010-62541831 62541834
  • 国际标准刊号：ISSN：1009-6124
  • 国内统一刊号：ISSN：11-4543/O1
  • 邮发代号:82-545
  • 获奖情况:
  • 国内外数据库收录:
  • 俄罗斯文摘杂志,美国数学评论（网络版）,德国数学文摘,荷兰文摘与引文数据库,美国工程索引,美国科学引文索引（扩展库）,英国科学文摘数据库
  • 被引量:125