Using R for Bayesian Spatial and Spatio-Temporal Health Modeling Contributor(s): Lawson, Andrew B. (Author) |
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ISBN: 0367490129 ISBN-13: 9780367490126 Publisher: CRC Press OUR PRICE: $152.00 Product Type: Hardcover - Other Formats Published: April 2021 |
Additional Information |
BISAC Categories: - Mathematics | Probability & Statistics - General - Medical | Epidemiology - Computers | Programming Languages - General |
Dewey: 610.21 |
LCCN: 2020049394 |
Physical Information: 0.69" H x 6.14" W x 9.21" (1.31 lbs) 284 pages |
Descriptions, Reviews, Etc. |
Publisher Description: 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. Features:
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. |