Applied Compositional Data Analysis With Worked Examples In R
Synopsis
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.Book details
- Edition:
- 1st ed. 2018
- Series:
- Springer Series in Statistics
- Author:
- Peter Filzmoser, Matthias Templ, Karel Hron
- ISBN:
- 9783319964225
- Related ISBNs:
- 9783319964201
- Publisher:
- Springer International Publishing
- Pages:
- N/A
- Reading age:
- Not specified
- Includes images:
- Yes
- Date of addition:
- 2019-07-21
- Usage restrictions:
- Copyright
- Copyright date:
- 2018
- Copyright by:
- Springer Nature Switzerland AG
- Adult content:
- No
- Language:
- English
- Categories:
- Computers and Internet, Earth Sciences, Mathematics and Statistics, Medicine, Nonfiction, Sociology