1st Edition
Bayesian Workflow
Part 1: From Bayesian inference to Bayesian workflow
1 Bayesian theory and Bayesian practice
2 Statistical modeling and workflow
3 Computational tools
4 Introduction to workflow: Modeling performance on a multiple choice exam
Part 2: Statistical workflow
5 Building statistical models
6 Using simulations to capture uncertainty
7 Prediction, generalization, and causal inference
8 Visualizing and checking fitted models
9 Comparing and improving models
10 Statistical inference and scientific inference
Part 3: Computational workflow
11 Fitting statistical models
12 Diagnosing and fixing problems with fitting
13 Approximate algorithms and approximate models
14 Simulation-based calibration checking
15 Statistical modeling as software development
Part 4: Case studies
16 Coding a series of models: Simulated data of movie ratings
17 Prior specification for regression models: Reanalysis of a sleep study
18 Predictive model checking and comparison: Clinical trial
19 Building up to a hierarchical model: Coronavirus testing
20 Using a fitted model for decision analysis: Mixture model for time series competition
21 Posterior predictive checking: Stochastic learning in dogs
22 Incremental development and testing: Black cat adoptions
23 Debugging a model: World Cup football
24 Leave-one-out cross validation model checking and comparison: Roaches
25 Model building and expansion: Golf putting
26 Model building with latent variables: Markov models for animal movement
27 Model building: Time-series decomposition for birthdays
28 Models for regression coefficients and variable selection: Student grades
29 Funnel problem with latent variables: No vehicles in the park
30 Computational challenge of multimodality: Differential equation for planetary motion
31 Simulation-based calibration checking in model development workflow
Biography
Andrew Gelman is a professor of statistics and political science at Columbia University
Aki Vehtari is a professor of computer science at Aalto University
Richard McElreath is the director of the Max Planck Institute for Evolutionary Anthropology
Daniel Simpson is a machine learning engineer at dottxt
Charles Margossian is an assistant professor of statistics at the University of British Columbia
Yuling Yao is an assistant professor of statistics at the University of Texas
Lauren Kennedy is a senior lecturer in mathematical science at the University of Adelaide
Jonah Gabry is an applied statistics researcher at Columbia University
Paul-Christian Bürkner is a professor of statistics at TU Dortmund University
Martin Modrák is a researcher in bioinformatics at Charles University
Vianey Leos Barajas is an assistant professor of statistical sciences at the University of Toronto
