A Student’s Guide to Bayesian Statistics by Lambert, Ben -- Read -- Imperial Library of Trantor

Index

Cover Half Title Publisher Note Title Page Copyright Page Acknowledgements Contents Online resources Acknowledgements About the Author 1 How Best to use this Book Part I An Introduction to Bayesian Inference 2 The Subjective Worlds of Frequentist and Bayesian Statistics 3 Probability – The Nuts and Bolts of Bayesian Inference Part II Understanding the Bayesian Formula 4 Likelihoods 5 Priors 6 The Devil is in the Denominator 7 The Posterior – The Goal of Bayesian Inference Part III Analytic Bayesian Methods 8 An Introduction to Distributions for the Mathematically Uninclined 9 Conjugate priors 10 Evaluation of model fit and hypothesis testing 11 Making Bayesian analysis objective? Part IV A practical guide to doing real-life Bayesian analysis: computational Bayes 12 Leaving conjugates behind: Markov chain Monte Carlo 13 Random Walk Metropolis 14 Gibbs sampling 15 Hamiltonian Monte Carlo 16 Stan Part V Hierarchical models and regression 17 Hierarchical models 18 Linear regression models 19 Generalised linear models and other animals References Index

Chief Librarian: Las Zenow <zenow@riseup.net>
Fork the source code from gitlab.