Non-regular statistical estimation
Non-regular statistical estimation
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非常规统计估计
DOI：
10.1007/978-1-4612-2554-6
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发表时间：
1995
期刊：
影响因子：
--
通讯作者：
K. Takeuchi
中科院分区：
文献类型：
--
作者：
M. Akahira;K. Takeuchi
为了得到统计估计理论中的许多经典结果，通常对所考虑的分布施加正则性条件。在小样本和大样本的估计理论中都有很好的规则条件集，如果这些规则条件中的任何一个不成立，那么接下来会发生什么是值得研究的“非正则估计”的字面意思是当某些或其他正则条件不成立时的统计估计理论。在这本专著中，作者提出了规律性条件的意义和含义的系统研究，并表明如何放松这些条件往往会导致令人惊讶的结论。他们的重点是考虑小样本结果，并展示病理例子如何在这个更广泛的框架内考虑。
In order to obtain many of the classical results in the theory of statistical estimation, it is usual to impose regularity conditions on the distributions under consideration. In small sample and large sample theories of estimation there are well established sets of regularity conditions, and it is worth while to examine what may follow if any one of these regularity conditions fail to hold." Non-regular estimation" literally means the theory of statistical estimation when some or other of the regularity conditions fail to hold. In this monograph, the authors present a systematic study of the meaning and implications of regularity conditions, and show how the relaxation of such conditions can often lead to surprising conclusions. Their emphasis is on considering small sample results and to show how pathological examples may be considered in this broader framework.