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Statistical Rethinking : A Bayesian Course with Examples in R and Stan[¾çÀå]

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Preface

Chapter 1. The Golem of Prague
Chapter 2. Small Worlds and Large Worlds
Chapter 3. Sampling the Imaginary
Chapter 4. Linear Models
Chapter 5. Multivariate Linear Models
Chapter 6. Overfitting, Regularization, and Information Criteria
Chapter 7. Interactions
Chapter 8. Markov Chain Monte Carlo
Chapter 9. Big Entropy and the Generalized Linear Model
Chapter 10. Counting and Classification
Chapter 11. Monsters and Mixtures
Chapter 12. Multilevel Models
Chapter 13. Adventures in Covariance
Chapter 14. Missing Data and Other Opportunities
Chapter 15. Horoscopes

Endnotes
Bibliography
Citation Index
Topic Index

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