Spatio-Temporal Methods in Environmental Epidemiology - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Spatio-Temporal Methods in Environmental Epidemiology write by Gavin Shaddick. This book was released on 2015-06-17. Spatio-Temporal Methods in Environmental Epidemiology available in PDF, EPUB and Kindle. Teaches Students How to Perform Spatio-Temporal Analyses within Epidemiological StudiesSpatio-Temporal Methods in Environmental Epidemiology is the first book of its kind to specifically address the interface between environmental epidemiology and spatio-temporal modeling. In response to the growing need for collaboration between statisticians and
Spatio–Temporal Methods in Environmental Epidemiology with R
Spatio–Temporal Methods in Environmental Epidemiology with R - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Spatio–Temporal Methods in Environmental Epidemiology with R write by Gavin Shaddick. This book was released on 2023-12-12. Spatio–Temporal Methods in Environmental Epidemiology with R available in PDF, EPUB and Kindle. Spatio-Temporal Methods in Environmental Epidemiology with R, like its First Edition, explores the interface between environmental epidemiology and spatio-temporal modeling. It links recent developments in spatio-temporal theory with epidemiological applications. Drawing on real-life problems, it shows how recent advances in methodology can assess the health risks associated with environmental hazards. The book's clear guidelines enable the implementation of the methodology and estimation of risks in practice. New additions to the Second Edition include: a thorough exploration of the underlying concepts behind knowledge discovery through data; a new chapter on extracting information from data using R and the tidyverse; additional material on methods for Bayesian computation, including the use of NIMBLE and Stan; new methods for performing spatio-temporal analysis and an updated chapter containing further topics. Throughout the book there are new examples, and the presentation of R code for examples has been extended. Along with these additions, the book now has a GitHub site (https://spacetime-environ.github.io/stepi2) that contains data, code and further worked examples. Features: • Explores the interface between environmental epidemiology and spatio-temporal modeling • Incorporates examples that show how spatio-temporal methodology can inform societal concerns about the effects of environmental hazards on health • Uses a Bayesian foundation on which to build an integrated approach to spatio-temporal modeling and environmental epidemiology • Discusses data analysis and topics such as data visualization, mapping, wrangling and analysis • Shows how to design networks for monitoring hazardous environmental processes and the ill effects of preferential sampling • Through the listing and application of code, shows the power of R, tidyverse, NIMBLE and Stan and other modern tools in performing complex data analysis and modeling Representing a continuing important direction in environmental epidemiology, this book – in full color throughout – underscores the increasing need to consider dependencies in both space and time when modeling epidemiological data. Readers will learn how to identify and model patterns in spatio-temporal data and how to exploit dependencies over space and time to reduce bias and inefficiency when estimating risks to health.
Spatio–Temporal Methods in Environmental Epidemiology with R
Spatio–Temporal Methods in Environmental Epidemiology with R - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Spatio–Temporal Methods in Environmental Epidemiology with R write by Gavin Shaddick. This book was released on 2023. Spatio–Temporal Methods in Environmental Epidemiology with R available in PDF, EPUB and Kindle.
Spatio-Temporal Statistics with R
Spatio-Temporal Statistics with R - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Spatio-Temporal Statistics with R write by Christopher K. Wikle. This book was released on 2019-02-18. Spatio-Temporal Statistics with R available in PDF, EPUB and Kindle. The world is becoming increasingly complex, with larger quantities of data available to be analyzed. It so happens that much of these "big data" that are available are spatio-temporal in nature, meaning that they can be indexed by their spatial locations and time stamps. Spatio-Temporal Statistics with R provides an accessible introduction to statistical analysis of spatio-temporal data, with hands-on applications of the statistical methods using R Labs found at the end of each chapter. The book: Gives a step-by-step approach to analyzing spatio-temporal data, starting with visualization, then statistical modelling, with an emphasis on hierarchical statistical models and basis function expansions, and finishing with model evaluation Provides a gradual entry to the methodological aspects of spatio-temporal statistics Provides broad coverage of using R as well as "R Tips" throughout. Features detailed examples and applications in end-of-chapter Labs Features "Technical Notes" throughout to provide additional technical detail where relevant Supplemented by a website featuring the associated R package, data, reviews, errata, a discussion forum, and more The book fills a void in the literature and available software, providing a bridge for students and researchers alike who wish to learn the basics of spatio-temporal statistics. It is written in an informal style and functions as a down-to-earth introduction to the subject. Any reader familiar with calculus-based probability and statistics, and who is comfortable with basic matrix-algebra representations of statistical models, would find this book easy to follow. The goal is to give as many people as possible the tools and confidence to analyze spatio-temporal data.
Using R for Bayesian Spatial and Spatio-Temporal Health Modeling
Using R for Bayesian Spatial and Spatio-Temporal Health Modeling - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Using R for Bayesian Spatial and Spatio-Temporal Health Modeling write by Andrew B. Lawson. This book was released on 2021-04-28. Using R for Bayesian Spatial and Spatio-Temporal Health Modeling available in PDF, EPUB and Kindle. 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: Review of R graphics relevant to spatial health data Overview of Bayesian methods and Bayesian hierarchical modeling as applied to spatial data Bayesian Computation and goodness-of-fit Review of basic Bayesian disease mapping models Spatio-temporal modeling with MCMC and INLA Special topics include multivariate models, survival analysis, missing data, measurement error, variable selection, individual event modeling, and infectious disease modeling Software for fitting models based on BRugs, Nimble, CARBayes and INLA Provides code relevant to fitting all examples throughout the book at a supplementary website 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.
