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＜電子ブック＞
Applied Spatial Data Analysis with R / by Roger S. Bivand, Edzer J. Pebesma, Virgilio Gómez-Rubio
(Use R!. ISSN:21975744)

版	1st ed. 2008.
出版者	(New York, NY : Springer New York : Imprint: Springer)
出版年	2008
本文言語	英語
大きさ	XIV, 376 p : online resource
著者標目	*Bivand, Roger S author Pebesma, Edzer J author Gómez-Rubio, Virgilio author SpringerLink (Online service)
件　名	LCSH:Epidemiology LCSH:Ecology  LCSH:Regional economics LCSH:Spatial economics LCSH:Environmental monitoring LCSH:Econometrics LCSH:Geography FREE:Epidemiology FREE:Ecology FREE:Regional and Spatial Economics FREE:Environmental Monitoring FREE:Econometrics FREE:Geography
一般注記	Handling Spatial Data in R -- Hello World: Introducing Spatial Data -- Classes for Spatial Data in R -- Visualising Spatial Data -- Spatial Data Import and Export -- Further Methods for Handling Spatial Data -- Customising Spatial Data Classes and Methods -- Analysing Spatial Data -- Spatial Point Pattern Analysis -- Interpolation and Geostatistics -- Areal Data and Spatial Autocorrelation -- Modelling Areal Data -- Disease Mapping Applied Spatial Data Analysis with R is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of interest to users who need to access and visualise spatial data. Data import and export for many file formats for spatial data are covered in detail, as is the interface between R and the open source GRASS GIS. The second part showcases more specialised kinds of spatial data analysis, including spatial point pattern analysis, interpolation and geostatistics, areal data analysis and disease mapping. The coverage of methods of spatial data analysis ranges from standard techniques to new developments, and the examples used are largely taken from the spatial statistics literature. All the examples can be run using R contributed packages available from the CRAN website, with code and additional data sets from the book's own website. This book will be of interest to researchers who intend to use R to handle, visualise, and analyse spatial data. It will also be of interest to spatial data analysts who do not use R, but who are interested in practical aspects of implementing software for spatial data analysis. It is a suitable companion book for introductory spatial statistics courses and for applied methods courses in a wide range of subjects using spatial data, including human and physical geography, geographical information systems, the environmental sciences, ecology, public health and disease control, economics, public administration and political science. The book has a website where coloured figures, complete code examples, data sets, and other support material may be found: http://www.asdar-book.org. The authors have taken part in writing and maintaining software for spatial data handling and analysis with R in concert since 2003. Roger Bivand is Professor of Geography in the Department of Economics at Norges Handelshøyskole, Bergen, Norway. Edzer Pebesma isProfessor of Geoinformatics at Westfälische Wilhelms-Universität, Münster, Germany. Virgilio Gómez-Rubio is Research Associate in the Department of Epidemiology and Public Health, Imperial College London, London, United Kingdom HTTP:URL=https://doi.org/10.1007/978-0-387-78171-6

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