Spatial and Spatio-temporal Bayesian Models with R - INLA

Spatial and Spatio-Temporal Bayesian Models withR-INLA provides a much needed, practically oriented& innovative presentation of the combination of Bayesianmethodology and spatial statistics. The authors combine anintroduction to Bayesian theory and methodology with a focus on thespatial and spatio­-temporal models used within the Bayesianframework and a series of practical examples which allow the readerto link the statistical theory presented to real data problems. Thenumerous examples from the fields of epidemiology, biostatisticsand social science all are coded in the R package R-INLA, which hasproven to be a valid alternative to the commonly used Markov ChainMonte Carlo simulations

• An Introduction to R for Spatial Analysis and Mapping
• Hierarchical Modeling and Analysis for Spatial Data (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)
• Applied Spatial Data Analysis with R (Use R!)
• R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
• Statistical Rethinking: A Bayesian Course with Examples in R and Stan (Chapman & Hall/CRC Texts in Statistical Science)
• An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
• Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan
• Bayesian Data Analysis (Chapman & Hall/CRC Texts in Statistical Science)
• Statistics for Spatio-Temporal Data
• The Book of Why: The New Science of Cause and Effect