Applied Compositional Data Analysis

Beschreibung

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.
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.
Fills the gap in the existing literature by providing a practical approach to compositional data analysis Presents a concise and easy-to-interpret methodology which guarantees a scale invariant analysis of data carrying relative information Uses the log-ratio approach, including various aspects of data processing Includes numerous real-world examples with implementations in R from a wide range of applications

Autor*in

Peter Filzmoser

Themen in »Applied Compositional Data Analysis«

Compositional data Applications of compositional data analysis Multivariate statistical methods Robust statistics Statistical environment R Statistical methodology for compositional data R package robCompositions Analyzing compositional data using R Methods for high-dimensional compositional data Compositional tables CoDa

Stimmen zu »Applied Compositional Data Analysis«

“Its great advantage is that it is very well written, easy to follow, very didactical, and self-contained. Its great advantage is that it is very well written, easy to follow, very didactical, and self-contained. … I would definitely recommend researchers to use this book, but they should be aware that compositional data analysis is not just based on simple transformations.” (Vera Pawlowsky-Glahn, Statistical Papers, Vol. 61, 2020)

“Its easy-to-read format and didactic layout are designed for researchers from different fields. … Applied Compositional Data Analysis is a nice book for scholars because it offers a wide spectrum of different types of statistical analysis.” (Jan Graffelman and Josep Antoni Martín-Fernández, Biometrical Journal, Vol. 62, 2020)

“The book is appropriate for graduate students with a basic statistical background as an introductory book to compositional data analysis using R as non-beginners. It can also be successfully used by PhD students, researchers and teachers requiring a consistent and through reference.” (Márta Ladányi, ISCB News, Vol. 68, December, 2019)

Details

Link teilen