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OverviewFull Product DetailsAuthor: Robert P. Haining , Guangquan LiPublisher: Taylor & Francis Inc Imprint: Chapman & Hall/CRC Weight: 3.320kg ISBN: 9781482237429ISBN 10: 1482237423 Pages: 640 Publication Date: 07 February 2020 Audience: Professional and scholarly , College/higher education , Professional & Vocational , Tertiary & Higher Education Format: Hardback Publisher's Status: Active Availability: In Print  This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of ContentsIntroduction. Thinking spatially, thinking statistically in the social and economic sciences. The nature of spatial data and the implications for statistical analysis. Exploratory analysis of spatial and spatial-temporal data. Bayesian regression modeling with spatial data. Introduction to the Bayesian approach to regression modeling with spatial data. Topics in spatial modeling. Further topics in spatial modeling. Bayesian regression modeling with spatial-temporal data. Generic issues in spatial-temporal modeling. Topics in spatial-temporal modeling. Appendices.ReviewsKnowledge on statistical theory and regression concepts are essential to read, comprehend, appreciate, and use the rich contents of this fascinating book. This well-written book is a good source for the Bayesian concepts and methods to practice the spatial-temporal analysis using R and WinBugs codes . . . I recommend this book to economics, health, statistics and computing professionals and researchers. ~ Ramalingam Shanmugam, Texas State University Knowledge on statistical theory and regression concepts are essential to read, comprehend, appreciate, and use the rich contents of this fascinating book. This well-written book is a good source for the Bayesian concepts and methods to practice the spatial-temporal analysis using R and WinBugs codes . . . I recommend this book to economics, health, statistics and computing professionals and researchers. -Ramalingam Shanmugam, Texas State University Overall, this book stands out among other spatial statistics books because of its ability to help readers develop practical modeling skills. Specifically, R code snippets are provided when specific R packages or functions are needed to handle geospatial data sets. The impressive number of case studies provide real-world guidance on how to adapt the same modeling strategies, with the accompanyingWinBUGS code, to other data sets. ... In summary, this book is an excellent resource for graduate students, statisticians, and quantitative researchers who are interested in analyzing areal spatial data. The inclusion of both spatial hierarchical models and econometrics models is particularly unique. Finally, the book's organization, contents, and writing style also encourage self-learning. -Howard H. Chang in Biometrics, March 2022 Knowledge on statistical theory and regression concepts are essential to read, comprehend, appreciate, and use the rich contents of this fascinating book. This well-written book is a good source for the Bayesian concepts and methods to practice the spatial-temporal analysis using R and WinBugs codes . . . I recommend this book to economics, health, statistics and computing professionals and researchers. ~ Ramalingam Shanmugam, Texas State University All statements in the book are clear and fully understandable for the reader. A large number of examples are accompanied by detailed explanations and R-codes. The book is a very good guide for researchers in the field of spatial and spatial-temporal data modelling for both beginners and professionals - Taras Lukashiv, International Society for Clinical Biostatistics, June 2021, Number 71 Author InformationRobert Haining is Emeritus Professor in Human Geography, University of Cambridge, England. He is the author of Spatial Data Analysis in the Social and Environmental Sciences (1990) and Spatial Data Analysis: Theory and Practice (2003). He is a Fellow of the RGS-IBG and of the Academy of Social Sciences. Guangquan Li is Senior Lecturer in Statistics in the Department of Mathematics, Physics and Electrical Engineering, Northumbria University, Newcastle, England. His research includes the development and application of Bayesian methods in the social and health sciences. He is a Fellow of the Royal Statistical Society. Tab Content 6Author Website:Countries AvailableAll regions |
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