000			04296nam a22005295i 4500
001			978-0-387-78171-6
003			DE-He213
005			20251006084418.0
007			cr nn 008mamaa
008			100301s2008 xxu| s |||| 0|eng d
020			_a9780387781716
020			_a99780387781716
024	7		_a10.1007/978-0-387-78171-6 _2doi
082	0	4	_a614.4 _223
100	1		_aBivand, Roger S. _eauthor.
245	1	0	_aApplied Spatial Data Analysis with R _h[electronic resource] / _cby Roger S. Bivand, Edzer J. Pebesma, Virgilio Gómez-Rubio.
264		1	_aNew York, NY : _bSpringer New York, _c2008.
300			_aXIV, 378p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aUse R!
505	0		_aHandling 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.
520			_aApplied 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 is Professor 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.
650		0	_aMEDICINE.
650		0	_aGEOLOGYXMATHEMATICS.
650		0	_aEPIDEMIOLOGY.
650		0	_aECOLOGY.
650		0	_aECONOMETRICS.
650	1	4	_aMEDICINE & PUBLIC HEALTH.
650	2	4	_aEPIDEMIOLOGY.
650	2	4	_aECOLOGY.
650	2	4	_aENVIRONMENTAL MONITORING/ANALYSIS.
650	2	4	_aQUANTITATIVE GEOLOGY.
650	2	4	_aECONOMETRICS.
700	1		_aPebesma, Edzer J. _eauthor.
700	1		_aGómez-Rubio, Virgilio. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387781709
830		0	_aUse R!
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-387-78171-6 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-SME
942			_2ddc _cER
999			_c59050 _d59050