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Applied Compositional Data Analysis - pr_262217

Applied Compositional Data Analysis

With Worked Examples in R

By Peter Filzmoser, Karel Hron, Matthias Templ

Hardback

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This book presents the statistical analysis of compositional data using the log-ratio approach. It includes a wide range of classical and robust statistical methods adapted for compositional data analysis, such as supervised and unsupervised methods like PCA, correlation analysis, classification and regression. In addition, it considers special data structures like high-dimensional compositions and compositional tables. The methodology introduced is also frequently compared to methods which ignore the specific nature of compositional data. It focuses on practical aspects of compositional data analysis rather than on detailed theoretical derivations, thus issues like graphical visualization and preprocessing (treatment of missing values, zeros, outliers and similar artifacts) form an important part of the book. Since it is primarily intended for researchers and students from applied fields like geochemistry, chemometrics, biology and natural sciences, economics, and social sciences, all the proposed methods are accompanied by worked-out examples in R using the package robCompositions.

Product code: 9783319964201

ISBN 9783319964201
Dimensions (HxWxD in mm) H235xW155
Series Springer Series in Statistics
No. Of Pages 280
Publisher Springer International Publishing AG
Edition 1st ed. 2018
This book presents the statistical analysis of compositional data using the log-ratio approach. It includes a wide range of classical and robust statistical methods adapted for compositional data analysis, such as supervised and unsupervised methods like PCA, correlation analysis, classification and regression.