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Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach
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TLDR
The second edition of this book is unique in that it focuses on methods for making formal statistical inference from all the models in an a priori set (Multi-Model Inference).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 * Summaryread more
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Transcriptome-wide noise controls lineage choice in mammalian progenitor cells
Hannah H. Chang,Martin Hemberg,Martin Hemberg,Mauricio Barahona,Donald E. Ingber,Sui Huang,Sui Huang +6 more
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A point process framework for relating neural spiking activity to spiking history, neural ensemble, and extrinsic covariate effects.
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