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About Using R for Bayesian Spatial and Spatio-Temporal Health Modeling (Chapman and Hall CRC The R Series)
Progressively more and more attention has been paid to how location affects health outcomes. The area of disease mapping focusses on these problems, and the Bayesian paradigm has a major role to play in the understanding of the complex interplay of context and individual predisposition in such studies of disease. Using R for Bayesian Spatial and Spatio-Temporal Health Modeling provides a major resource for those interested in applying Bayesian methodology in small area health data studies. The book fills a void in the literature and available software, providing a crucial link for students and professionals alike to engage in the analysis of spatial and spatio-temporal health data from a Bayesian perspective using R. The book emphasizes the use of MCMC via Nimble, BRugs, and CARBAyes, but also includes INLA for comparative purposes. In addition, a wide range of packages useful in the analysis of geo-referenced spatial data are employed and code is provided. It will likely become a key reference for researchers and students from biostatistics, epidemiology, public health, and environmental science.
Detailed Information
| Author: | Andrew B Lawson |
|---|---|
| Publication Year: | 2021 |
| ISBN: | 9780367490126 |
| Pages: | 300 |
| Language: | English |
| File Size: | 7.7 |
| Format: | |
| Price: | FREE |
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