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Titre : Functional data analysis with R and MATLAB Type de document : livre Auteurs : J. O. Ramsay, Auteur ; Gilles Hooker, Auteur ; Spencer Graves, Auteur Editeur : Dordrecht : Springer AnnÃ©e de publication : 2009 Collection : Use R! Importance : 207 p. ISBN/ISSN/EAN : 978-0-387-98184-0 Prix : 69.99 USD Langues : Anglais ( eng)Mots-clÃ©s : Computer programs Data processing R (Computer program language) MATLAB (Computer program language) Case studies RÃ©sumÃ© : Scientists often collect samples of curves and other functional observations, and develop models where parameters are also functions. This volume in the UseR! Series is aimed at a wide range of readers, and especially those who would like apply these techniques to their research problems. It complements Functional Data Analysis, Second Edition and Applied Functional Data Analysis: Methods and Case Studies by providing computer code in both the R and Matlab languages for a set of data analyses that showcase functional data analysis techniques. The authors make it easy to get up and running in new applications by adapting the code for the examples, and by being able to access the details of key functions within these pages. This book is accompanied by additional web-based support at http://www.functionaldata.org for applying existing functions and developing new ones in either language. The companion 'fda' package for R includes script files to reproduce nearly all the examples in the book including all but one of the 76 figures. En ligne : https://doi.org/10.1007/978-0-387-98185-7 Functional data analysis with R and MATLAB [livre] / J. O. Ramsay, Auteur ; Gilles Hooker, Auteur ; Spencer Graves, Auteur . - Dordrecht : Springer, 2009 . - 207 p.. - (Use R!) .ISBN: 978-0-387-98184-0 : 69.99 USD

Langues : Anglais (eng)

Mots-clÃ©s : Computer programs Data processing R (Computer program language) MATLAB (Computer program language) Case studies RÃ©sumÃ© : Scientists often collect samples of curves and other functional observations, and develop models where parameters are also functions. This volume in the UseR! Series is aimed at a wide range of readers, and especially those who would like apply these techniques to their research problems. It complements Functional Data Analysis, Second Edition and Applied Functional Data Analysis: Methods and Case Studies by providing computer code in both the R and Matlab languages for a set of data analyses that showcase functional data analysis techniques. The authors make it easy to get up and running in new applications by adapting the code for the examples, and by being able to access the details of key functions within these pages. This book is accompanied by additional web-based support at http://www.functionaldata.org for applying existing functions and developing new ones in either language. The companion 'fda' package for R includes script files to reproduce nearly all the examples in the book including all but one of the 76 figures. En ligne : https://doi.org/10.1007/978-0-387-98185-7 ## Exemplaires (1)

Code-barres Cote Support Localisation Section DisponibilitÃ© 69536 RAM_11_69536 Livre Salle des ouvrages 11_Mathématiques Sorti jusqu'au 25/05/2043Statistical computing with R / Rizzo, M.L. (2008)

Titre : Statistical computing with R Type de document : livre Auteurs : Rizzo, M.L. Editeur : Boca Raton : Chapman & Hall/CRC AnnÃ©e de publication : 2008 Collection : Computer science and data analysis series Importance : 399 p. ISBN/ISSN/EAN : 978-1-58488-545-0 Langues : Anglais ( eng)Mots-clÃ©s : R (Computer program language) Statistical methods RÃ©sumÃ© : Computational statistics and statistical computing are two areas that employ computational, graphical, and numerical approaches to solve statistical problems, making the versatile R language an ideal computing environment for these fields. One of the first books on these topics to feature R, Statistical Computing with R covers the traditional core material of computational statistics, with an emphasis on using the R language via an examples-based approach. Suitable for an introductory course in computational statistics or for self-study, it includes R code for all examples and R notes to help explain the R programming concepts. After an overview of computational statistics and an introduction to the R computing environment, the book reviews some basic concepts in probability and classical statistical inference. Each subsequent chapter explores a specific topic in computational statistics. These chapters cover the simulation of random variables from probability distributions, the visualization of multivariate data, Monte Carlo integration and variance reduction methods, Monte Carlo methods in inference, bootstrap and jackknife, permutation tests, Markov chain Monte Carlo (MCMC) methods, and density estimation. The final chapter presents a selection of examples that illustrate the application of numerical methods using R functions. Focusing on implementation rather than theory, this text serves as a balanced, accessible introduction to computational statistics and statistical computing. [RÃ©sumÃ© Ã©diteur] Statistical computing with R [livre] / Rizzo, M.L. . - Boca Raton : Chapman & Hall/CRC, 2008 . - 399 p.. - (Computer science and data analysis series) .ISBN: 978-1-58488-545-0

Langues : Anglais (eng)

Mots-clÃ©s : R (Computer program language) Statistical methods RÃ©sumÃ© : Computational statistics and statistical computing are two areas that employ computational, graphical, and numerical approaches to solve statistical problems, making the versatile R language an ideal computing environment for these fields. One of the first books on these topics to feature R, Statistical Computing with R covers the traditional core material of computational statistics, with an emphasis on using the R language via an examples-based approach. Suitable for an introductory course in computational statistics or for self-study, it includes R code for all examples and R notes to help explain the R programming concepts. After an overview of computational statistics and an introduction to the R computing environment, the book reviews some basic concepts in probability and classical statistical inference. Each subsequent chapter explores a specific topic in computational statistics. These chapters cover the simulation of random variables from probability distributions, the visualization of multivariate data, Monte Carlo integration and variance reduction methods, Monte Carlo methods in inference, bootstrap and jackknife, permutation tests, Markov chain Monte Carlo (MCMC) methods, and density estimation. The final chapter presents a selection of examples that illustrate the application of numerical methods using R functions. Focusing on implementation rather than theory, this text serves as a balanced, accessible introduction to computational statistics and statistical computing. [RÃ©sumÃ© Ã©diteur] ## Exemplaires (1)

Code-barres Cote Support Localisation Section DisponibilitÃ© 68239 RIZ_11_68239 Livre Salle des ouvrages 11_Mathématiques Sorti jusqu'au 25/05/2043Analysis of phylogenetics and evolution with R / Paradis, E. (2006)

Titre : Analysis of phylogenetics and evolution with R Type de document : livre Auteurs : Paradis, E., Auteur Editeur : New York : Springer AnnÃ©e de publication : 2006 Collection : Use R! Importance : 211 p. ISBN/ISSN/EAN : 978-0-387-32914-7 Langues : Anglais ( eng)Mots-clÃ©s : Evolution Phylogenetics R (Computer program language) RÃ©sumÃ© : The increasing availability of molecular and genetic databases coupled with the growing power of computers gives biologists opportunities to address new issues, such as the patterns of molecular evolution, and re-assess old ones, such as the role of adaptation in species diversification. This book integrates a wide variety of data analysis methods into a single and flexible interface: the R language. This open source language is available for a wide range of computer systems and has been adopted as a computational environment by many authors of statistical software. Adopting R as a main tool for phylogenetic analyses will ease the workflow in biologists' data analyses, ensure greater scientific repeatability, and enhance the exchange of ideas and methodological developments. Graduate students and researchers in evolutionary biology can use this book as a reference for data analyses, whereas researchers in bioinformatics interested in evolutionary analyses will learn how to implement these methods in R. The book starts with a presentation of different R packages and gives a short introduction to R for phylogeneticists unfamiliar with this language. The basic phylogenetic topics are covered: manipulation of phylogenetic data, phylogeny estimation, tree drawing, phylogenetic comparative methods, and estimation of ancestral characters. The chapter on tree drawing uses R's powerful graphical environment. A section deals with the analysis of diversification with phylogenies, one of the author's favorite research topics. The last chapter is devoted to the development of phylogenetic methods with R and interfaces with other languages (C and C++). Some exercises conclude these chapters. Analysis of phylogenetics and evolution with R [livre] / Paradis, E., Auteur . - New York : Springer, 2006 . - 211 p.. - (Use R!) .ISBN: 978-0-387-32914-7

Langues : Anglais (eng)

Mots-clÃ©s : Evolution Phylogenetics R (Computer program language) RÃ©sumÃ© : The increasing availability of molecular and genetic databases coupled with the growing power of computers gives biologists opportunities to address new issues, such as the patterns of molecular evolution, and re-assess old ones, such as the role of adaptation in species diversification. This book integrates a wide variety of data analysis methods into a single and flexible interface: the R language. This open source language is available for a wide range of computer systems and has been adopted as a computational environment by many authors of statistical software. Adopting R as a main tool for phylogenetic analyses will ease the workflow in biologists' data analyses, ensure greater scientific repeatability, and enhance the exchange of ideas and methodological developments. Graduate students and researchers in evolutionary biology can use this book as a reference for data analyses, whereas researchers in bioinformatics interested in evolutionary analyses will learn how to implement these methods in R. The book starts with a presentation of different R packages and gives a short introduction to R for phylogeneticists unfamiliar with this language. The basic phylogenetic topics are covered: manipulation of phylogenetic data, phylogeny estimation, tree drawing, phylogenetic comparative methods, and estimation of ancestral characters. The chapter on tree drawing uses R's powerful graphical environment. A section deals with the analysis of diversification with phylogenies, one of the author's favorite research topics. The last chapter is devoted to the development of phylogenetic methods with R and interfaces with other languages (C and C++). Some exercises conclude these chapters. ## Exemplaires (1)

Code-barres Cote Support Localisation Section DisponibilitÃ© 68108 PAR_11_68108 Livre Salle des ouvrages 11_Mathématiques Disponible

Titre : The R book Type de document : livre Auteurs : Michael J. Crawley, Auteur Mention d'Ã©dition : 2nd ed. Editeur : Chichester, U.K. : Wiley AnnÃ©e de publication : 2013 Importance : 1051 p. ISBN/ISSN/EAN : 978-0-470-97392-9 Prix : 68.00 GBP Note gÃ©nÃ©rale : 2 ex.; Voir aussi la 1ère éd. de 2007 aux cotes 68177, 68339, 68367, 68469 et 68557/11 Langues : Anglais ( eng)Mots-clÃ©s : Analysis of variance Data analysis Non-linear regression R (Computer program language) Spatial statistics Statistical methods RÃ©sumÃ© : La 4Ã¨me de couv. indique : Hugely successful and popular text presenting an extensive and comprehensive guide for all R users

The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research.

This edition:

*Features full colour text and extensive graphics throughout.

*Introduces a clear structure with numbered section headings to help readers locate information more efficiently.

*Looks at the evolution of R over the past five years.

*Features a new chapter on Bayesian Analysis and Meta-Analysis.

*Presents a fully revised and updated bibliography and reference section.

*Is supported by an accompanying website allowing examples from the text to be run by the user.Note de contenu : Download all the Executable text files (a bundle of 268 small text files) : http://www.bio.ic.ac.uk/research/mjcraw/therbook/index.htm En ligne : https://www.wiley.com/en-gb/The+R+Book%2C+2nd+Edition-p-9780470973929 The R book [livre] / Michael J. Crawley, Auteur . - 2nd ed. . - Chichester, U.K. : Wiley, 2013 . - 1051 p.ISBN: 978-0-470-97392-9 : 68.00 GBP

2 ex.; Voir aussi la 1ère éd. de 2007 aux cotes 68177, 68339, 68367, 68469 et 68557/11

Langues : Anglais (eng)

Mots-clÃ©s : Analysis of variance Data analysis Non-linear regression R (Computer program language) Spatial statistics Statistical methods RÃ©sumÃ© : La 4Ã¨me de couv. indique : Hugely successful and popular text presenting an extensive and comprehensive guide for all R users

The R language is recognized as one of the most powerful and flexible statistical software packages, enabling users to apply many statistical techniques that would be impossible without such software to help implement such large data sets. R has become an essential tool for understanding and carrying out research.

This edition:

*Features full colour text and extensive graphics throughout.

*Introduces a clear structure with numbered section headings to help readers locate information more efficiently.

*Looks at the evolution of R over the past five years.

*Features a new chapter on Bayesian Analysis and Meta-Analysis.

*Presents a fully revised and updated bibliography and reference section.

*Is supported by an accompanying website allowing examples from the text to be run by the user.Note de contenu : Download all the Executable text files (a bundle of 268 small text files) : http://www.bio.ic.ac.uk/research/mjcraw/therbook/index.htm En ligne : https://www.wiley.com/en-gb/The+R+Book%2C+2nd+Edition-p-9780470973929 ## Exemplaires (2)

Code-barres Cote Support Localisation Section DisponibilitÃ© 69720 CRA_11_69720 Livre Salle des ouvrages 11_Mathématiques Sorti jusqu'au 25/05/204369746 CRA_11_69746 Livre Salle des ouvrages 11_Mathématiques Sorti jusqu'au 13/08/2049

Titre : A first course in statistical programming with R Type de document : livre Auteurs : W. John Braun, Auteur ; Duncan J. Murdoch, Auteur Mention d'Ã©dition : 1st ed. Editeur : Cambridge, UK : Cambridge University Press AnnÃ©e de publication : 2007 Importance : 163 p. ISBN/ISSN/EAN : 978-0-521-69424-7 Langues : Anglais ( eng)Mots-clÃ©s : Data analysis Languages Learning R (Computer program language) Statistical analysis RÃ©sumÃ© : This is the only introduction you'll need to start programming in R, the open-source language that is free to download, and lets you adapt the source code for your own requirements. Co-written by one of the R Core Development Team, and by an established R author, this book comes with real R code that complies with the standards of the language. Unlike other introductory books on the ground-breaking R system, this book emphasizes programming, including the principles that apply to most computing languages, and techniques used to develop more complex projects. Learning the language is made easier by the frequent exercises and end-of-chapter reviews that help you progress confidently through the book. Solutions, datasets and any errata will be available from the book's web site. The many examples, all from real applications, make it particularly useful for anyone working in practical data analysis. En ligne : http://books.google.com/books?id=aodgVNrU_8IC&printsec=frontcover&hl=fr A first course in statistical programming with R [livre] / W. John Braun, Auteur ; Duncan J. Murdoch, Auteur . - 1st ed. . - Cambridge, UK : Cambridge University Press, 2007 . - 163 p.ISBN: 978-0-521-69424-7

Langues : Anglais (eng)

Mots-clÃ©s : Data analysis Languages Learning R (Computer program language) Statistical analysis RÃ©sumÃ© : This is the only introduction you'll need to start programming in R, the open-source language that is free to download, and lets you adapt the source code for your own requirements. Co-written by one of the R Core Development Team, and by an established R author, this book comes with real R code that complies with the standards of the language. Unlike other introductory books on the ground-breaking R system, this book emphasizes programming, including the principles that apply to most computing languages, and techniques used to develop more complex projects. Learning the language is made easier by the frequent exercises and end-of-chapter reviews that help you progress confidently through the book. Solutions, datasets and any errata will be available from the book's web site. The many examples, all from real applications, make it particularly useful for anyone working in practical data analysis. En ligne : http://books.google.com/books?id=aodgVNrU_8IC&printsec=frontcover&hl=fr ## Exemplaires (1)

Code-barres Cote Support Localisation Section DisponibilitÃ© 68262 BRA_11_68262 Livre Salle des ouvrages 11_Mathématiques DisponiblePermalinkPermalinkIntegrated population models: theory and ecological applications with R and JAGS / Michael Schaub (2022)

PermalinkHandbook of trait-based ecology: from theory to R tools / Francesco de Bello (2021)

PermalinkMastering shiny: build interactive apps, reports, and dashboards powered by R / Hadley Wickham (2021)

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