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Auteur Edzer J. Pebesma |
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Code-barres Cote Support Localisation Section Disponibilité E000424 211 BIV Ouvrage ENSAE 2. Statistique Sorti jusqu'au 30/04/2018 E000425 211 BIV Ouvrage ENSAE 2. Statistique Disponible I000976 879 BIVA Ouvrage Ensai 8. Informatique - Traitement de l'information Disponible Applied Spatial Data Analysis with R / Roger S. Bivand / Berlin ; Heidelberg (DEU) ; New York : Springer (2013)
Titre : Applied Spatial Data Analysis with R Type de document : document électronique Auteurs : Roger S. Bivand ; SpringerLink (Online service) Editeur : Berlin ; Heidelberg (DEU) ; New York : Springer Année de publication : 2013 Collection : Use R!, ISSN 2197-5736 num. 10 Importance : XVIII, 405 p. 121 illus., 89 illus. in color Présentation : online resource ISBN/ISSN/EAN : 978-1-4614-7618-4 Langues : Anglais (eng) Descripteurs : Analyse spatiale , Biostatistique La biostatistique (appelée aussi biométrie) est l'application des statistiques à un large éventail de sujets en biologie. Cela englobe la conception des expériences biologiques (dans la médecine et l'agriculture), la collecte des informations, la compilation et analyse des données chiffrées de ces expériences, l'interprétation des résultats en vue d'avancer une conclusion., Logiciel statistique RTags : Statistics Cartography Medicine Health Sciences Statistics for Engineering Physics Computer Science Chemistry and Earth Sciences Environmental Monitoring/Analysis Quantitative Geography Résumé : 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 Note de contenu : 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 Permalink : http://genes.bibli.fr/index.php?lvl=notice_display&id=108188 Applied Spatial Data Analysis with R [document électronique] / Roger S. Bivand ; SpringerLink (Online service)
ISBN : 978-1-4614-7618-4
Langues : Anglais (eng)
Descripteurs : Analyse spatiale , Biostatistique La biostatistique (appelée aussi biométrie) est l'application des statistiques à un large éventail de sujets en biologie. Cela englobe la conception des expériences biologiques (dans la médecine et l'agriculture), la collecte des informations, la compilation et analyse des données chiffrées de ces expériences, l'interprétation des résultats en vue d'avancer une conclusion., Logiciel statistique RTags : Statistics Cartography Medicine Health Sciences Statistics for Engineering Physics Computer Science Chemistry and Earth Sciences Environmental Monitoring/Analysis Quantitative Geography Résumé : 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 Note de contenu : 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 Permalink : http://genes.bibli.fr/index.php?lvl=notice_display&id=108188
Titre : Applied spatial data analysis with R Type de document : texte imprimé Auteurs : Roger S. Bivand, ; Edzer J. Pebesma, ; Virgilio Gómez-Rubio, Mention d'édition : 2nd edition Editeur : Berlin ; Heidelberg (DEU) ; New York : Springer Année de publication : 2013 Collection : Use R!, ISSN 2197-5736 num. 10 Importance : XVIII-405 p. Présentation : fig., tabl. Format : 24 cm ISBN/ISSN/EAN : 978-1-4614-7617-7 Note générale : Bibliogr. p. 367-385. Index Langues : Anglais (eng) Descripteurs : Analyse des données , Analyse spatiale , Logiciel statistique R , Logiciel statistique SAS, SPAD, SPSS, R, STATA, STATlab, TIMElab
STATGRAPHICS, SYSTAT, STATISTICA, BMDP...Index. décimale : 87 Logiciels statistiques En ligne : http://www.springer.com/statistics/life+sciences%2C+medicine+%26+health/book/978 [...] Permalink : http://genes.bibli.fr/index.php?lvl=notice_display&id=107076 Applied spatial data analysis with R [texte imprimé] / Roger S. Bivand, ; Edzer J. Pebesma, ; Virgilio Gómez-Rubio, . - 2nd edition . - Berlin ; Heidelberg (DEU) ; New York : Springer, 2013 . - XVIII-405 p. : fig., tabl. ; 24 cm. - (Use R!, ISSN 2197-5736; 10) .
ISBN : 978-1-4614-7617-7
Bibliogr. p. 367-385. Index
Langues : Anglais (eng)
Descripteurs : Analyse des données , Analyse spatiale , Logiciel statistique R , Logiciel statistique SAS, SPAD, SPSS, R, STATA, STATlab, TIMElab
STATGRAPHICS, SYSTAT, STATISTICA, BMDP...Index. décimale : 87 Logiciels statistiques En ligne : http://www.springer.com/statistics/life+sciences%2C+medicine+%26+health/book/978 [...] Permalink : http://genes.bibli.fr/index.php?lvl=notice_display&id=107076 Réservation
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Accompagne Applied spatial data analysis with R / Roger S. Bivand / Berlin ; Heidelberg (DEU) ; New York : Springer (2008)
Titre : Applied Spatial Data Analysis with R Type de document : document électronique Auteurs : Roger S. Bivand ; SpringerLink (Online service) Editeur : Berlin ; Heidelberg (DEU) ; New York : Springer Année de publication : 2008 Collection : Use R!, ISSN 2197-5736 Importance : XIV, 376 p Présentation : online resource ISBN/ISSN/EAN : 978-0-387-78171-6 Langues : Anglais (eng) Tags : Medicine Epidemiology Geography Ecology Econometrics Regional economics Spatial economics Medicine & Public Health Regional/Spatial Science Environmental Monitoring/Analysis Résumé : 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 Note de contenu : 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 Permalink : http://genes.bibli.fr/index.php?lvl=notice_display&id=118142 Applied Spatial Data Analysis with R [document électronique] / Roger S. Bivand ; SpringerLink (Online service)
Accompagne Applied spatial data analysis with R / Roger S. Bivand / Berlin ; Heidelberg (DEU) ; New York : Springer (2008)
ISBN : 978-0-387-78171-6
Langues : Anglais (eng)
Tags : Medicine Epidemiology Geography Ecology Econometrics Regional economics Spatial economics Medicine & Public Health Regional/Spatial Science Environmental Monitoring/Analysis Résumé : 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 Note de contenu : 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 Permalink : http://genes.bibli.fr/index.php?lvl=notice_display&id=118142
Titre : Applied statistical genetics with R : for population-based association studies Type de document : texte imprimé Auteurs : Andrea S. Foulkes ; Edzer J. Pebesma ; Virgilio Gómez-Rubio Editeur : Berlin ; Heidelberg (DEU) ; New York : Springer Année de publication : 2009 Collection : Use R!, ISSN 2197-5736 Importance : XXIII-252 p. ISBN/ISSN/EAN : 978-0-387-89553-6 Note générale : Bibliogr. p. 227-235. Index Langues : Anglais (eng) Descripteurs : Biostatistique La biostatistique (appelée aussi biométrie) est l'application des statistiques à un large éventail de sujets en biologie. Cela englobe la conception des expériences biologiques (dans la médecine et l'agriculture), la collecte des informations, la compilation et analyse des données chiffrées de ces expériences, l'interprétation des résultats en vue d'avancer une conclusion., Econométrie , Logiciel statistique R , Santé , Statistique mathématiqueTags : Life Sciences Medicine Health Sciences Biostatistics Biomedical and Life Sciences Index. décimale : 254 Biostatistique - Biométrie En ligne : http://www.springer.com/new+%26+forthcoming+titles+%28default%29/book/978-0-387- [...] Permalink : http://genes.bibli.fr/index.php?lvl=notice_display&id=88614 Applied statistical genetics with R : for population-based association studies [texte imprimé] / Andrea S. Foulkes ; Edzer J. Pebesma ; Virgilio Gómez-Rubio . - Berlin ; Heidelberg (DEU) ; New York : Springer, 2009 . - XXIII-252 p.. - (Use R!, ISSN 2197-5736) .
ISBN : 978-0-387-89553-6
Bibliogr. p. 227-235. Index
Langues : Anglais (eng)
Descripteurs : Biostatistique La biostatistique (appelée aussi biométrie) est l'application des statistiques à un large éventail de sujets en biologie. Cela englobe la conception des expériences biologiques (dans la médecine et l'agriculture), la collecte des informations, la compilation et analyse des données chiffrées de ces expériences, l'interprétation des résultats en vue d'avancer une conclusion., Econométrie , Logiciel statistique R , Santé , Statistique mathématiqueTags : Life Sciences Medicine Health Sciences Biostatistics Biomedical and Life Sciences Index. décimale : 254 Biostatistique - Biométrie En ligne : http://www.springer.com/new+%26+forthcoming+titles+%28default%29/book/978-0-387- [...] Permalink : http://genes.bibli.fr/index.php?lvl=notice_display&id=88614 Réservation
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Code-barres Cote Support Localisation Section Disponibilité I000678 254 FOUL Ouvrage Ensai 2. Statistique Disponible I000956 254 FOUL Ouvrage Ensai 2. Statistique Sorti jusqu'au 17/09/2018
