Using R for Bayesian spatial and spatio-temporal health modeling / Andrew B. Lawson.
By: Lawson, Andrew (Andrew B.) [author.].
Material type:
BookSeries: Chapman & Hall/CRC the R series.Publisher: Boca Raton : Chapman & Hall/CRC, 2021Edition: 1st.Description: 1 online resource : illustrations (black and white).Content type: still image | text Media type: computer Carrier type: online resourceISBN: 9781000376722 (ePub ebook); 1000376729 (ePub ebook); 9781000376708 (PDF ebook); 1000376702 (PDF ebook); 9781003043997 (ebook); 1003043992 (ebook).Subject(s): Medical statistics -- Data processing | Medical mapping -- Data processing | Medical statistics -- Computer programs | Geospatial data -- Computer processing | Geographic information systems | Information modeling -- Simulation methods | R (Computer program language) | Bayesian statistical decision theory | MATHEMATICS / Probability & Statistics / General | MEDICAL / EpidemiologyDDC classification: 610.21 Online resources: Taylor & Francis | OCLC metadata license agreement Summary: "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"--
1. Introduction and Data Sets
2. R Graphics and Spatial Health Data
3. Bayesian Hierarchical Models
4. Computation
5. Bayesian model Goodness of Fit Criteria
6. Bayesian Disease Mapping Models
Part I Basic Software Approaches
7. BRugs/OpenBUGS
8. Nimble
9. CARBayes
10. INLA and R-INLA
11. Clustering, Latent Variable and Mixture Modeling
12. Spatio-Temporal Modeling with MCMC
13. Spatio-Temporal Modeling with INLA
Part II Some Advanced and Special topics
14. Multivariate Models
15. Survival Modeling
16. Missingness, Measurement Error and Variable Selection
17. Individual Event Modeling
18. Infectious Disease Modeling
"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"--
OCLC-licensed vendor bibliographic record.
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