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Model Selection and Multimodel Inference

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Cover of 'Model Selection and Multimodel Inference'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Information and Likelihood Theory: A Basis for Model Selection and Inference
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    Chapter 3 Basic Use of the Information-Theoretic Approach
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    Chapter 4 Formal Inference From More Than One Model: Multimodel Inference (MMI)
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    Chapter 5 Monte Carlo Insights and Extended Examples
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    Chapter 6 Advanced Issues and Deeper Insights
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    Chapter 7 Statistical Theory and Numerical Results
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    Chapter 8 Summary
Attention for Chapter 2: Information and Likelihood Theory: A Basis for Model Selection and Inference
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