Case Studies in Applied Bayesian Data Science: Cirm Jean-Morlet Chair, Fall 2018 (Paperback, 2020)

Introduction.-Part A. Reviews.- Jahan et al: A review of Bayesian statistical models for big data.-Goan: Bayesian neural networks ? an introduction and review.- Wu & Robert: Markov chain Monte Carlo algorithms for Bayesian computation, a review and some generalisations.- Sutton: Bayesian variable selection.-Moores et al: Big data and intractable likelihoods.-Part B. Real World Case Studies.-B1. Case Studies in Health.-Cespedes et al: A Bayesian hierarchical approach to jointly model cortical thickness and covariance networks.-White et al: Clustering action potential spikes: Insights on the use of overfitted finite mixture models and Dirichlet process mixture models.-Aswi et al. Spatio-temporal analysis of dengue fever in Makassar Indonesia: a comparison of models based on CARBayes.-Cramb et al. A comparison of Bayesian spatial models for cancer incidence at a small area level: theory and performance.-Thomas et al: An ensemble approach to modelling the combined effect of risk factors on age at Parkinson’s Disease onset.-Harden et al: Workplace health and workplace wellness: synergistic or disconnected?-Tierney et al: Bayesian modelling to assist inference on health outcomes in occupational health surveillance.-B2. Case Studies in Ecology.- Davis et al: Bayesian Networks for modelling human-wildlife conflict in conservation.-Sequeira et al: Bayesian optimization of predictive biodiversity models using repeated observations and less frequently observed predictors.-Vercelloni et al: Thresholds of coral densities that support Great Barrier Reef biodiversity.-Ullah et al: Application of Bayesian mixture models to satellite images and estimating the risk of fire-ant incursion in the identified geographical cluster