How to walk on statistical mandalas as a population ecologist
How to walk on statistical mandalas as a population ecologist
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作为人口生态学家如何在统计曼荼罗上行走
DOI：
10.1007/s10144-015-0532-z
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发表时间：
2016
影响因子：
1.7
通讯作者：
Y.
中科院分区：
文献类型：
--
作者：
Toquenaga;Y.
我们这些被认为擅长处理统计数据的人口生态学家，经常对我们应该采用哪种统计方法来处理这些令人讨厌的数据感到困惑。在统计学中有一些相互冲突的范式和许多相关的方法。在科学领域占主导地位的经典频率论者的方法受到了新来者的严厉批评：贝叶斯和证据统计。但是，这两个新来者也都有弱点。致力于不同统计方法的研究人员正在寻找能够相互妥协的软着陆点。统计推断的关键方面是判别模型选择和参数估计。可能性和费雪信息在这两个过程中都起着重要作用。作为妥协过程的概述，我将在这里介绍由m.l.锥度、j.m. Ponciano、r.m. Dorazio和K. Yamamura撰写的三篇论文，题为“种群生态学的贝叶斯、fisher、误差和证据统计方法”。本专题基于2014年10月11日在日本筑波举行的一次研讨会
We population ecologists who are believed to be good at dealing with statistics often get confused about what kinds of statistical methods we should apply to our nuisance data. There are a couple of conflicting paradigms and many associated methods in statistics. Classical frequentists’ approaches that have dominated in science have been severely criticized by the newcomers: Bayesian and evidential statistics. But, both newcomers also have weak points. Researchers devoted to different statistical approaches are seeking soft landing places where they can compromise each other. Key aspects of statistical inference are discriminating model selection and parameter estimation. Likelihood and Fisher information play important roles in both processes. As an overview of the compromise processes, here I will introduce three contributing papers by M. L. Taper, J. M. Ponciano, R. M. Dorazio, and K. Yamamura for the special feature entitled “Bayesian, Fisherian, error, and evidential statistical approaches for population ecology.” This special feature is based on a symposium held in Tsukuba, Japan, on 11 October 2014