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    Broschiertes Buch

"Chemometrics with R" offers readers an accessible introduction to the world of multivariate statistics in the life sciences, providing a complete description of the general data analysis paradigm, from exploratory analysis to modeling to validation. Several more specific topics from the area of chemometrics are included in a special section. The corresponding R code is provided for all the examples in the book; scripts, functions and data are available in a separate, publicly available R package. For researchers working in the life sciences, the book can also serve as an easy-to-use primer on R.…mehr

Produktbeschreibung
"Chemometrics with R" offers readers an accessible introduction to the world of multivariate statistics in the life sciences, providing a complete description of the general data analysis paradigm, from exploratory analysis to modeling to validation. Several more specific topics from the area of chemometrics are included in a special section. The corresponding R code is provided for all the examples in the book; scripts, functions and data are available in a separate, publicly available R package. For researchers working in the life sciences, the book can also serve as an easy-to-use primer on R.
  • Produktdetails
  • Use R!
  • Verlag: Springer, Berlin
  • Artikelnr. des Verlages: 80028749
  • Erscheinungstermin: 1. Februar 2011
  • Englisch
  • Abmessung: 237mm x 156mm x 22mm
  • Gewicht: 468g
  • ISBN-13: 9783642178405
  • ISBN-10: 3642178405
  • Artikelnr.: 32462739
Autorenporträt
Ron Wehrens (1966) obtained a PhD in Chemometrics at the Radboud University Nijmegen, The Netherlands. He was a lecturer in Analytical Chemistry at the University of Twente, and later an associated professor at the Radboud University Nijmegen. Since January 2010, he is group leader in Biostatistics and Data Analysis at the Fondazione Edmund Mach in San Michele all'Adige, Italy.
Inhaltsangabe
Introduction.- Part I Preliminaries: Data.- Preprocessing.- Part II Exploratory Analysis: Principal Component Analysis.- Self-Organizing Maps.- Clustering.- Part III Modelling: Classification.- Multivariate Regression.- Part IV Model Inspection: Validation.- Variable Selection.- Part V Applications: Chemometric.- Part VI Appendices: R packages Used in This Book.- References.- Index.