Applied Spatial Data Analysis with R / Roger S. Bivand (2008)  

Público ISBD Título : Applied Spatial Data Analysis with R Tipo de documento: documento electrónico Autores: Roger S. Bivand ; SpringerLink (Online service) ; Edzer J. Pebesma ; Virgilio Gómez Rubio Editorial: New York, NY : Springer New York Fecha de publicación: 2008 Colección: Use R!, ISSN 2197-5736 Número de páginas: XIV, 376 p Il.: online resource ISBN/ISSN/DL: 978-0-387-78171-6 Idioma : Inglés (eng) Palabras clave: Medicine  Epidemiology  Geography  Ecology  Econometrics  Regional  economics  Spatial  &  Public  Health  Regional/Spatial  Science  Environmental  Monitoring/Analysis  Geography,  general Clasificación: 51 Matemáticas Resumen: 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 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 Nota de contenido: 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 En línea: http://dx.doi.org/10.1007/978-0-387-78171-6 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34246 Applied Spatial Data Analysis with R [documento electrónico] / Roger S. Bivand ; SpringerLink (Online service) ; Edzer J. Pebesma ; Virgilio Gómez Rubio . - New York, NY : Springer New York, 2008 . - XIV, 376 p : online resource. - (Use R!, ISSN 2197-5736) . ISBN : 978-0-387-78171-6 Idioma : Inglés (eng) Palabras clave: Medicine  Epidemiology  Geography  Ecology  Econometrics  Regional  economics  Spatial  &  Public  Health  Regional/Spatial  Science  Environmental  Monitoring/Analysis  Geography,  general Clasificación: 51 Matemáticas Resumen: 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 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 Nota de contenido: 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 En línea: http://dx.doi.org/10.1007/978-0-387-78171-6 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34246

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Applied Spatial Data Analysis with R / Roger S. Bivand (2013)  

Público ISBD Título : Applied Spatial Data Analysis with R Tipo de documento: documento electrónico Autores: Roger S. Bivand ; SpringerLink (Online service) ; Edzer J. Pebesma ; Virgilio Gómez Rubio Editorial: New York, NY : Springer New York Fecha de publicación: 2013 Otro editor: Imprint: Springer Colección: Use R!, ISSN 2197-5736 num. 10 Número de páginas: XVIII, 405 p. 121 illus., 89 illus. in color Il.: online resource ISBN/ISSN/DL: 978-1-4614-7618-4 Idioma : Inglés (eng) Palabras clave: Statistics  Geography  for  Life  Sciences,  Medicine,  Health  Sciences  Engineering,  Physics,  Computer  Science,  Chemistry  and  Earth  Statistics,  general  Environmental  Monitoring/Analysis  Geography, Clasificación: 51 Matemáticas Resumen: Applied Spatial Data Analysis with R, Second Edition, 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 and the handling of spatio-temporal data. 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. Compared to the first edition, the second edition covers the more systematic approach towards handling spatial data in R, as well as a number of important and widely used CRAN packages that have appeared since the first edition.   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 science and geoinformatics, the environmental sciences, ecology, public health and disease control, economics, public administration and political science.   The book has a website where 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 Nota de contenido: Preface 2nd edition -- Preface 1st edition -- 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 -- Classes for spatio-temporal Data -- Spatial Point Pattern Analysis -- Interpolation and Geostatistics -- Modelling Areal Data -- Disease Mapping En línea: http://dx.doi.org/10.1007/978-1-4614-7618-4 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32360 Applied Spatial Data Analysis with R [documento electrónico] / Roger S. Bivand ; SpringerLink (Online service) ; Edzer J. Pebesma ; Virgilio Gómez Rubio . - New York, NY : Springer New York : Imprint: Springer, 2013 . - XVIII, 405 p. 121 illus., 89 illus. in color : online resource. - (Use R!, ISSN 2197-5736; 10) . ISBN : 978-1-4614-7618-4 Idioma : Inglés (eng) Palabras clave: Statistics  Geography  for  Life  Sciences,  Medicine,  Health  Sciences  Engineering,  Physics,  Computer  Science,  Chemistry  and  Earth  Statistics,  general  Environmental  Monitoring/Analysis  Geography, Clasificación: 51 Matemáticas Resumen: Applied Spatial Data Analysis with R, Second Edition, 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 and the handling of spatio-temporal data. 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. Compared to the first edition, the second edition covers the more systematic approach towards handling spatial data in R, as well as a number of important and widely used CRAN packages that have appeared since the first edition.   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 science and geoinformatics, the environmental sciences, ecology, public health and disease control, economics, public administration and political science.   The book has a website where 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 Nota de contenido: Preface 2nd edition -- Preface 1st edition -- 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 -- Classes for spatio-temporal Data -- Spatial Point Pattern Analysis -- Interpolation and Geostatistics -- Modelling Areal Data -- Disease Mapping En línea: http://dx.doi.org/10.1007/978-1-4614-7618-4 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32360

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