A guide to Bayesian model selection for ecologists
A guide to Bayesian model selection for ecologists
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DOI：
10.1890/14-0661.1
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发表时间：
2015-02-01
影响因子：
6.1
通讯作者：
Hobbs, N. T.
中科院分区：
文献类型：
--
作者：
Hooten, M. B.;Hobbs, N. T.
模型选择和贝叶斯方法在生态学研究中的使用稳步上升的趋势表明，这两种推理方法对于现代模型和数据分析都很重要。然而，在教授贝叶斯方法和与我们的研究同事合作时，我们注意到对现有的关于贝叶斯模型选择和多模型推理的文献普遍感到不满。刚接触贝叶斯方法的学生和研究人员很快就会发现，已发表的关于模型选择的建议在处理分析选项时往往是优先的，经常提倡一种特定的方法而不是其他方法。最近出现的许多关于贝叶斯建模的文章和教科书为贝叶斯框架中模型选择的相关方法提供了可喜的背景，但其中大多数要么范围非常狭窄，要么生态学家无法接触到。此外，贝叶斯模型选择方法的方法论细节在文献中分布得很少，出现在许多不同领域的期刊上。我们用这本指南的目的是浓缩大量关于贝叶斯方法的模型选择和多模型推理的文献，并专门为定量生态学家尽可能中立地介绍它。我们还揭示了一些与模型选择直接相关的重要和基本概念，这些概念在生态文献中似乎没有引起注意。在整个过程中，我们只提供了一个最小的哲学讨论，而是倾向于检查方法的广度以及它们的实际优势和劣势。本指南为使用贝叶斯方法的生态学家提供参考，以便他们能够更好地了解自己的选择，并做出最符合其推理目标的知情选择。
The steady upward trend in the use of model selection and Bayesian methods in ecological research has made it clear that both approaches to inference are important for modern analysis of models and data. However, in teaching Bayesian methods and in working with our research colleagues, we have noticed a general dissatisfaction with the available literature on Bayesian model selection and multimodel inference. Students and researchers new to Bayesian methods quickly find that the published advice on model selection is often preferential in its treatment of options for analysis, frequently advocating one particular method above others. The recent appearance of many articles and textbooks on Bayesian modeling has provided welcome background on relevant approaches to model selection in the Bayesian framework, but most of these are either very narrowly focused in scope or inaccessible to ecologists. Moreover, the methodological details of Bayesian model selection approaches are spread thinly throughout the literature, appearing in journals from many different fields. Our aim with this guide is to condense the large body of literature on Bayesian approaches to model selection and multimodel inference and present it specifically for quantitative ecologists as neutrally as possible. We also bring to light a few important and fundamental concepts relating directly to model selection that seem to have gone unnoticed in the ecological literature. Throughout, we provide only a minimal discussion of philosophy, preferring instead to examine the breadth of approaches as well as their practical advantages and disadvantages. This guide serves as a reference for ecologists using Bayesian methods, so that they can better understand their options and can make an informed choice that is best aligned with their goals for inference.