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The book focuses on information-theoretic methods for analyzing empirical data, emphasizing model selection and multimodel inference for more robust conclusions. It aims to enhance understanding for graduate students and researchers across various scientific fields. The second edition features improved presentation, highlighted key concepts, and a new chapter, while reorganizing existing content for better flow. Additionally, it includes updated technical material and over 100 new references, reflecting insights gained from seminars and workshops.
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Model Selection and Multimodel Inference, David R. Anderson, Kenneth P. Burnham
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- Pubblicato
- 2010
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