Bringing Bayesian Models to Life

✍ Scribed by Mevin B. Hooten, Trevor J. Hefley

• Publisher: CRC Press
• Year: 2019
• Tongue: English
• Leaves: 591
• Category: Library

✦ Table of Contents

Cover
Half Title
Title Page
Copyright Page
Table of Contents
Preface
Acknowledgments
Authors
SECTION I: Background
Chapter 1: Bayesian Models
1.1 Introduction and Statistical Notation
1.2 Probability Concepts
1.3 Modeling Concepts
1.4 Additional Concepts and Reading
Chapter 2: Numerical Integration
2.1 Bayesian Integrals
2.2 Numerical Quadrature
2.3 Additional Concepts and Reading
Chapter 3: Monte Carlo
3.1 Sampling
3.2 Monte Carlo Integration
3.3 Additional Concepts and Reading
Chapter 4: Markov Chain Monte Carlo
4.1 Metropolis-Hastings
4.2 Metropolis-Hastings in Practice
4.3 Proposal Distributions
4.4 Gibbs Sampling
4.5 Additional Concepts and Reading
Chapter 5: Importance Sampling
5.1 Additional Concepts and Reading
SECTION II: Basic Models and Concepts
Chapter 6: Bernoulli-Beta
6.1 MCMC with Symmetric Proposal Distributions
6.2 MCMC with Proposal Distributions Based on Transformations
6.3 Additional Concepts and Reading
Chapter 7: Normal-Normal
7.1 Additional Concepts and Reading
Chapter 8: Normal-Inverse Gamma
8.1 Additional Concepts and Reading
Chapter 9: Normal-Normal-Inverse Gamma
9.1 Additional Concepts and Reading
SECTION III: Intermediate Models and Concepts
Chapter 10: Mixture Models
10.1 Additional Concepts and Reading
Chapter 11: Linear Regression
11.1 Additional Concepts and Reading
Chapter 12: Posterior Prediction
12.1 Additional Concepts and Reading
Chapter 13: Model Comparison
13.1 Additional Concepts and Reading
Chapter 14: Regularization
14.1 Additional Concepts and Reading
Chapter 15: Bayesian Model Averaging
15.1 Additional Concepts and Reading
Chapter 16: Time Series Models
16.1 Univariate Autoregressive Models
16.2 Autoregressive Models for Populations
16.3 Prediction with Time Series Models
16.4 Multivariate Autoregressive Models for Animal Movement
16.5 Additional Concepts and Reading
Chapter 17: Spatial Models
17.1 Geostatistical Models
17.2 Bayesian Kriging
17.3 Areal Data Models
17.4 Additional Concepts and Reading
SECTION IV: Advanced Models and Concepts
Chapter 18: Quantile Regression
18.1 Quantile Models for Continuous Data
18.2 Additional Concepts and Reading
Chapter 19: Hierarchical Models
19.1 Hierarchical Gaussian Models
19.2 Two-Stage Model Fitting Algorithms
19.3 Additional Concepts and Reading
Chapter 20: Binary Regression
20.1 Generalized Linear Models
20.2 Logistic Regression
20.3 Probit Regression
20.4 Quantile Models for Binary Data
20.5 Additional Concepts and Reading
Chapter 21: Count Data Regression
21.1 Poisson Regression
21.2 Resource Selection Functions and Species Distribution Models
21.3 Step Selection Functions
21.4 Poisson Time Series Models
21.5 Model Checking
21.6 Negative Binomial Regression
21.7 Quantile Models for Count Data
21.8 Binomial Models
21.9 Additional Concepts and Reading
Chapter 22: Zero-Inflated Models
22.1 Mixture Models for Excess Zeros
22.2 Zero-Inflated Poisson Models
22.3 Zero-Inflated Negative Binomial Models
22.4 Additional Concepts and Reading
Chapter 23: Occupancy Models
23.1 Simple Occupancy Models
23.2 General Occupancy Models
23.3 Probit Occupancy Models
23.4 Additional Concepts and Reading
Chapter 24: Abundance Models
24.1 Capture-Recapture Models
24.2 Distance Sampling Models
24.3 Survival Models
24.4 N-Mixture Models
24.5 Additional Concepts and Reading
SECTION V: Expert Models and Concepts
Chapter 25: Integrated Population Models
25.1 Data Reconciliation
25.2 False Positive Models with Auxiliary Data
25.3 Population Vital Rate IPMs
25.4 Additional Concepts and Reading
Chapter 26: Spatial Occupancy Models
26.1 Additional Concepts and Reading
Chapter 27: Spatial Capture-Recapture Models
27.1 Additional Concepts and Reading
Chapter 28: Spatio-temporal Models
28.1 Multivariate Time Series Models
28.2 Mechanistic Spatio-temporal Models
28.3 Additional Concepts and Reading
Chapter 29: Hamiltonian Monte Carlo
29.1 Additional Concepts and Reading
Tips and Tricks
Glossary
References
Probability Distributions
Index