Bringing bayesian models to life/ Mevin B Hooten and Trevor J Hefley

Includes bibliographical references and index

Section 1 Background -- Chapter 1. Bayesian models -- Chapter 2 Numerical integration -- Chapter 3 Monte Carlo -- Chapter 4 Markov Chain Monte Carlo -- Chapter 5 Importance sampling -- Section II Basic models and concepts -- Chapter 6 Bernoulli Beta -- Chapter 7 Normal-normal -- Chapter 8 Normal-inverse gamma -- Chapter 9 Normal-normal-inverse gamma -- Section III Intermediate mdels and concepts -- Chapter 10 Mixture models -- Chapter 11 Linear regression -- Chapter 12 Posterior prediction -- chapter 13 Model comparison -- chapter 14 regularization -- Chapter 15 Bayesian model averaging -- Chapter 16 Time series models -- Chapter 17 Spatial models -- Section IV Advanced models an concepts -- Chapter 18 Quantile regression -- Chapter 19 Hierarchical models -- Chapter 20 Bunary regression -- Chapter 21 Count data regression -- Chapter 22 Zero-inflated models -- Chapter 23 Occupancy models -- Chapter 24 Abundance models -- Section V Expert models and concepts -- Chapter 25 Integrated population models -- Chapter 26 Spatial occupancy models -- Chapter 27 Spatial capture-recapture models -- 28 Spatio-temporal models -- Chapter 29 Hamiltonian Monte Carlo