Using R for Bayesian Spatial and Spatio-Temporal Health Modeling (ePub)
(Sprache: Englisch)
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.
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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.
Autoren-Porträt von Andrew B. Lawson
Dr Lawson is Professor of Biostatistics in the Division of Biostatistics and Bioinformatics, Department of Public Health Sciences, College of Medicine, MUSC and is an MUSC Distinguished Professor Emeritus and ASA Fellow. His PhD was in Spatial Statistics from the University of St. Andrews, UK.He has over 190 journal papers on the subject of spatial epidemiology, spatial statistics and related areas. In addition to a number of book chapters, he is the author of 10 books in areas related to spatial epidemiology and health surveillance. The most recent of these is Lawson, A.B. et al (eds) (2016) Handbook of Spatial Epidemiology. CRC Press, New York, and in 2018 a 3rd edition of Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology CRC Press. He has acted as an advisor in disease mapping and risk assessment for the World Health Organization (WHO) and is the founding editor of the Elsevier journal Spatial and Spatio-temporal Epidemiology. Dr Lawson has delivered many short courses in different locations over the last 20 years on Bayesian Disease Mapping with OpenBUGS, INLA, and Nimble, and more general spatial epidemiology topics.
Web site: http://people.musc.edu/~abl6/
Bibliographische Angaben
- Autor: Andrew B. Lawson
- 2021, 1. Auflage, 300 Seiten, Englisch
- Verlag: Taylor & Francis
- ISBN-10: 1000376729
- ISBN-13: 9781000376722
- Erscheinungsdatum: 28.04.2021
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- Dateiformat: ePub
- Grösse: 11 MB
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Sprache:
Englisch
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