Fisher信息量是统计推断的基本概念, 在统计分析的许多领域中都发挥着重要作用. 文章分别在简单随机抽样,排序集抽样(RSS), 极值RSS (ERSS)和中位数RSS (MRSS)下研究了skew-normal分布中对应样本所含偏度参数的Fisher信息量.数值结果显示,同等样本容量不同类型完美排序集样本比简单随机样本提供更多的信息.数值结果也显示所有信息都会因排序出错而减少.
Abstract
Fisher information is a fundamental concept of statistical inference and plays an important role in many areas of statistical analysis. In this article, Fisher information in the corresponding samples about the skewness parameter from skewnormal distribution under simple random sampling, ranked set sampling (RSS), extreme RSS (ERSS) and median RSS (MRSS) will be respectively studied. The numerical results show that different types of perfect ranked set sample carry more information than a simple random sample of equivalent size. The numerical results also show all information will decrease as rank error.
关键词
排序集抽样 /
极值排序集抽样 /
中位数排序集抽样 /
Fisher信息量
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Key words
Ranked set sampling /
extreme ranked set sampling /
median ranked set sampling /
fisher information number
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中图分类号：
62F07
62F10
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基金
国家自然科学基金(11901236, 12261036),湖南省自然科学面上基金项目(2022JJ30469),湖南省教育厅重点项目(21A0328),2020年湖南省教学改革项目(HNJG-2020-0552),湖南省学位与研究生教学改革研究项目(2022JGZD051)和湖南省青年骨干教师项目(湘教通〔2020〕43号)资助课题.
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