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Titre : Numerical ecology with R Type de document : livre Auteurs : Daniel Borcard, Auteur ; François Gillet, Auteur ; Pierre Legendre, Auteur Mention d'édition : 2nd ed. Editeur : New York : Springer Année de publication : 2018 Collection : Use R! Importance : 435 p. ISBN/ISSN/EAN : 978-3-319-71403-5 Note générale : Voir aussi la 1ère ed. de 2011 aux cotes 69116/11 et 69319/11; All the necessary data files, the scripts used in the chapters, as well as the extra R functions and packages written by the authors, can be downloaded from a web page accessible through the Springer web site (http://adn.biol.umontreal.ca/~numericalecology/numecolR/). Langues : Anglais (eng) Mots-clés : Data processing Ecology Mathematics Multivariate analysis R (Computer program language) Statistical methods Résumé : Le site éditeur indique : This new edition of Numerical Ecology with R guides readers through an applied exploration of the major methods of multivariate data analysis, as seen through the eyes of three ecologists. It provides a bridge between a textbook of numerical ecology and the implementation of this discipline in the R language. The book begins by examining some exploratory approaches. It proceeds logically with the construction of the key building blocks of most methods, i.e. association measures and matrices, and then submits example data to three families of approaches: clustering, ordination and canonical ordination. The last two chapters make use of these methods to explore important and contemporary issues in ecology: the analysis of spatial structures and of community diversity. The aims of methods thus range from descriptive to explanatory and predictive and encompass a wide variety of approaches that should provide readers with an extensive toolbox that can address a wide palette of questions arising in contemporary multivariate ecological analysis. The second edition of this book features a complete revision to the R code and offers improved procedures and more diverse applications of the major methods. It also highlights important changes in the methods and expands upon topics such as multiple correspondence analysis, principal response curves and co-correspondence analysis. New features include the study of relationships between species traits and the environment, and community diversity analysis.
This book is aimed at professional researchers, practitioners, graduate students and teachers in ecology, environmental science and engineering, and in related fields such as oceanography, molecular ecology, agriculture and soil science, who already have a background in general and multivariate statistics and wish to apply this knowledge to their data using the R language, as well as people willing to accompany their disciplinary learning with practical applications. People from other fields (e.g. geology, geography, paleoecology, phylogenetics, anthropology, the social and education sciences, etc.) may also benefit from the materials presented in this book. Users are invited to use this book as a teaching companion at the computer. All the necessary data files, the scripts used in the chapters, as well as extra R functions and packages written by the authors of the book, are available online (URL: http://adn.biol.umontreal.ca/~numericalecology/numecolR/).En ligne : https://doi.org/10.1007/978-3-319-71404-2 Numerical ecology with R [livre] / Daniel Borcard, Auteur ; François Gillet, Auteur ; Pierre Legendre, Auteur . - 2nd ed. . - New York : Springer, 2018 . - 435 p.. - (Use R!) .
ISBN : 978-3-319-71403-5
Voir aussi la 1ère ed. de 2011 aux cotes 69116/11 et 69319/11; All the necessary data files, the scripts used in the chapters, as well as the extra R functions and packages written by the authors, can be downloaded from a web page accessible through the Springer web site (http://adn.biol.umontreal.ca/~numericalecology/numecolR/).
Langues : Anglais (eng)
Mots-clés : Data processing Ecology Mathematics Multivariate analysis R (Computer program language) Statistical methods Résumé : Le site éditeur indique : This new edition of Numerical Ecology with R guides readers through an applied exploration of the major methods of multivariate data analysis, as seen through the eyes of three ecologists. It provides a bridge between a textbook of numerical ecology and the implementation of this discipline in the R language. The book begins by examining some exploratory approaches. It proceeds logically with the construction of the key building blocks of most methods, i.e. association measures and matrices, and then submits example data to three families of approaches: clustering, ordination and canonical ordination. The last two chapters make use of these methods to explore important and contemporary issues in ecology: the analysis of spatial structures and of community diversity. The aims of methods thus range from descriptive to explanatory and predictive and encompass a wide variety of approaches that should provide readers with an extensive toolbox that can address a wide palette of questions arising in contemporary multivariate ecological analysis. The second edition of this book features a complete revision to the R code and offers improved procedures and more diverse applications of the major methods. It also highlights important changes in the methods and expands upon topics such as multiple correspondence analysis, principal response curves and co-correspondence analysis. New features include the study of relationships between species traits and the environment, and community diversity analysis.
This book is aimed at professional researchers, practitioners, graduate students and teachers in ecology, environmental science and engineering, and in related fields such as oceanography, molecular ecology, agriculture and soil science, who already have a background in general and multivariate statistics and wish to apply this knowledge to their data using the R language, as well as people willing to accompany their disciplinary learning with practical applications. People from other fields (e.g. geology, geography, paleoecology, phylogenetics, anthropology, the social and education sciences, etc.) may also benefit from the materials presented in this book. Users are invited to use this book as a teaching companion at the computer. All the necessary data files, the scripts used in the chapters, as well as extra R functions and packages written by the authors of the book, are available online (URL: http://adn.biol.umontreal.ca/~numericalecology/numecolR/).En ligne : https://doi.org/10.1007/978-3-319-71404-2 Exemplaires (2)
Code-barres Cote Support Localisation Section Disponibilité 69587 BOR_11_69587 Livre Salle des ouvrages 11_Mathématiques Sorti jusqu'au 25/05/2043 69588 BOR_11_69588 Livre Salle des ouvrages 11_Mathématiques Disponible
Titre : Statistical analysis of network data with R Type de document : livre Auteurs : Eric Kolaczyk, Auteur ; Gábor Csárdi, Auteur Editeur : New York : Springer Année de publication : 2014 Collection : Use R! num. 65 Importance : 207 p. ISBN/ISSN/EAN : 978-1-4939-0982-7 Langues : Anglais (eng) Mots-clés : Mathematical models Network analysis R (Computer program language) Statistical methods Résumé : Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries. Measurement and analysis are integral components of network research. As a result, statistical methods play a critical role in network analysis. This book is the first of its kind in network research. It can be used as a stand-alone resource in which multiple R packages are used to illustrate how to conduct a wide range of network analyses, from basic manipulation and visualization, to summary and characterization, to modeling of network data. The central package is igraph, which provides extensive capabilities for studying network graphs in R. This text builds on Eric D. Kolaczyk's book Statistical Analysis of Network Data (Springer, 2009) En ligne : http://www.springer.com/cn/book/9781493909827 Statistical analysis of network data with R [livre] / Eric Kolaczyk, Auteur ; Gábor Csárdi, Auteur . - New York : Springer, 2014 . - 207 p.. - (Use R!; 65) .
ISBN : 978-1-4939-0982-7
Langues : Anglais (eng)
Mots-clés : Mathematical models Network analysis R (Computer program language) Statistical methods Résumé : Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries. Measurement and analysis are integral components of network research. As a result, statistical methods play a critical role in network analysis. This book is the first of its kind in network research. It can be used as a stand-alone resource in which multiple R packages are used to illustrate how to conduct a wide range of network analyses, from basic manipulation and visualization, to summary and characterization, to modeling of network data. The central package is igraph, which provides extensive capabilities for studying network graphs in R. This text builds on Eric D. Kolaczyk's book Statistical Analysis of Network Data (Springer, 2009) En ligne : http://www.springer.com/cn/book/9781493909827 Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité 69375 KOL_11_69375 Livre Salle des ouvrages 11_Mathématiques Sorti jusqu'au 25/05/2043
Titre : Applied spatial data analysis with R Type de document : livre Auteurs : Roger S. Bivand, Auteur ; Edzer Pebesma, Auteur ; Virgilio Gómez-Rubio, Auteur Mention d'édition : 2nd ed. Editeur : New York : Springer Année de publication : 2013 Collection : Use R! Importance : 405 p. ISBN/ISSN/EAN : 978-1-4614-7617-7 Note générale : Code, datat sets and errata will be posted on the book website (http://www.asdar-book.org) Langues : Anglais (eng) Mots-clés : Data processing R (Computer program language) Spatial analysis (Statistics) En ligne : http://dx.doi.org/10.1007/978-1-4614-7618-4 Applied spatial data analysis with R [livre] / Roger S. Bivand, Auteur ; Edzer Pebesma, Auteur ; Virgilio Gómez-Rubio, Auteur . - 2nd ed. . - New York : Springer, 2013 . - 405 p.. - (Use R!) .
ISBN : 978-1-4614-7617-7
Code, datat sets and errata will be posted on the book website (http://www.asdar-book.org)
Langues : Anglais (eng)
Mots-clés : Data processing R (Computer program language) Spatial analysis (Statistics) En ligne : http://dx.doi.org/10.1007/978-1-4614-7618-4 Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité 69222 BIV_11_69222 Livre Salle des ouvrages 11_Mathématiques Disponible
Titre : Numerical ecology with R Type de document : livre Auteurs : Daniel Borcard, Auteur ; François Gillet, Auteur ; Pierre Legendre, Auteur Editeur : New York : Springer Année de publication : 2011 Collection : Use R! Importance : 306 p. ISBN/ISSN/EAN : 978-1-4419-7975-9 Note générale : Voir aussi la 2ème éd. de 2018 aux cotes 69587/11 et 69588/11; This URL provides the data sets, R scripts, R functions and several useful links related to the book entitled "Numerical Ecology with R ('http://adn.biol.umontreal.ca/~numericalecology/numecolR/') Langues : Anglais (eng) Mots-clés : Data processing Ecology Mathematics Multivariate analysis R (Computer program language) Statistical methods Note de contenu : Livre disponible en version électronique dans le cadre d’une licence nationale (accès réservé via identifiants CNRS et/ou universités Montpellier UM, UPVM) En ligne : https://doi.org/10.1007/978-1-4419-7976-6 Numerical ecology with R [livre] / Daniel Borcard, Auteur ; François Gillet, Auteur ; Pierre Legendre, Auteur . - New York : Springer, 2011 . - 306 p.. - (Use R!) .
ISBN : 978-1-4419-7975-9
Voir aussi la 2ème éd. de 2018 aux cotes 69587/11 et 69588/11; This URL provides the data sets, R scripts, R functions and several useful links related to the book entitled "Numerical Ecology with R ('http://adn.biol.umontreal.ca/~numericalecology/numecolR/')
Langues : Anglais (eng)
Mots-clés : Data processing Ecology Mathematics Multivariate analysis R (Computer program language) Statistical methods Note de contenu : Livre disponible en version électronique dans le cadre d’une licence nationale (accès réservé via identifiants CNRS et/ou universités Montpellier UM, UPVM) En ligne : https://doi.org/10.1007/978-1-4419-7976-6 Exemplaires (2)
Code-barres Cote Support Localisation Section Disponibilité 69116 BOR_11_69116 Livre Salle des ouvrages 11_Mathématiques Sorti jusqu'au 25/05/2043 69319 BOR_11_69319 Livre Salle des ouvrages 11_Mathématiques Disponible
Titre : Introducing Monte Carlo methods with R Type de document : livre Auteurs : Christian P. Robert, Auteur ; George Casella, Auteur Editeur : New York : Springer Année de publication : 2010 Collection : Use R! Importance : 283 p. ISBN/ISSN/EAN : 978-1-4419-1575-7 Note générale : DOI: 10.1007/978-1-4419-1576-4 Langues : Anglais (eng) Mots-clés : Computer programs Data processing Markov processes Mathematical statistics Monte Carlo method R (Computer program language) En ligne : http://dx.doi.org/10.1007/978-1-4419-1576-4 Introducing Monte Carlo methods with R [livre] / Christian P. Robert, Auteur ; George Casella, Auteur . - New York : Springer, 2010 . - 283 p.. - (Use R!) .
ISBN : 978-1-4419-1575-7
DOI: 10.1007/978-1-4419-1576-4
Langues : Anglais (eng)
Mots-clés : Computer programs Data processing Markov processes Mathematical statistics Monte Carlo method R (Computer program language) En ligne : http://dx.doi.org/10.1007/978-1-4419-1576-4 Exemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité 68758 ROB_11_68758 Livre Salle des ouvrages 11_Mathématiques Disponible PermalinkPermalink
