AIC and the challenge of complexity: A case study from ecology
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- 作者：Remington J. Molla ; rjmoll@msu.edu" class="auth_mail" title="E-mail the corresponding author ; Daniel Steelb ; Robert A. Montgomerya ; c
- 关键词：Akaike's Information Criterion ; Complexity ; Ecology ; Modeling ; Model selection ; Simplicity
- 刊名：Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of Biological and Biomedical Sciences
- 出版年：2016
- 出版时间：December 2016
- 年：2016
- 卷：60
- 期：Complete
- 页码：35-43
- 全文大小：385 K
文摘
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Predictive accuracy has justified simplicity in model selection.
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Model selection criteria generally entail a uniformity of nature assumption.
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Complexity threatens this assumption when predictions are extrapolated.
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This challenges simplicity's epistemic value when modeling complexity.
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In complex systems simplicity might improve explanation rather than prediction.