Applied Compositional Data Analysis With Worked Examples in R

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...

Full description

Bibliographic Details
Main Authors: Filzmoser, Peter, Hron, Karel (Author), Templ, Matthias (Author)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2018, 2018
Edition:1st ed. 2018
Series:Springer Series in Statistics
Subjects:
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
LEADER 02958nmm a2200361 u 4500
001 EB001854641
003 EBX01000000000000001018943
005 00000000000000.0
007 cr|||||||||||||||||||||
008 181201 ||| eng
020 |a 9783319964225 
100 1 |a Filzmoser, Peter 
245 0 0 |a Applied Compositional Data Analysis  |h Elektronische Ressource  |b With Worked Examples in R  |c by Peter Filzmoser, Karel Hron, Matthias Templ 
250 |a 1st ed. 2018 
260 |a Cham  |b Springer International Publishing  |c 2018, 2018 
300 |a XVII, 280 p. 74 illus., 57 illus. in color  |b online resource 
505 0 |a Preface -- Acknowledgements -- Compositional data as a methodological concept -- Analyzing compositional data using R -- Geometrical properties of compositional data -- Exploratory data analysis and visualization -- First steps for a statistical analysis -- Cluster analysis -- Principal component analysis -- Correlation analysis -- Discriminant analysis -- Regression analysis -- Methods for high-dimensional compositional data -- Compositional tables -- Preprocessing issues -- Index.- 
653 |a Statistical Theory and Methods 
653 |a Statistics  
653 |a Statistics and Computing/Statistics Programs 
653 |a Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences 
653 |a Geochemistry 
653 |a Geochemistry 
653 |a Statistics for Life Sciences, Medicine, Health Sciences 
653 |a Statistics for Social Sciences, Humanities, Law 
700 1 |a Hron, Karel  |e [author] 
700 1 |a Templ, Matthias  |e [author] 
041 0 7 |a eng  |2 ISO 639-2 
989 |b Springer  |a Springer eBooks 2005- 
490 0 |a Springer Series in Statistics 
856 4 0 |u https://doi.org/10.1007/978-3-319-96422-5?nosfx=y  |x Verlag  |3 Volltext 
082 0 |a 519.5 
520 |a 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