Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach 论文
2003Journal of Wildlife Management引用 42166
Neural Networks and ApplicationsStatistical and Computational ModelingScientific Measurement and Uncertainty Evaluation
摘要
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