Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach
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Abstract
Introduction * Information and Likelihood Theory: A Basis for Model Selection and Inference * Basic Use of the Information-Theoretic Approach * Formal Inference From More Than One Model: Multi-Model Inference (MMI) * Monte Carlo Insights and Extended Examples * Statistical Theory and Numerical Results * Summary
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Keywords
- Selection (genetic algorithm)
- Inference
- Computer science
- Model selection
- Artificial intelligence
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