Applied Compositional Data Analysis: With Worked Examples In R (1st ed. 2018) (Springer Series in Statistics)

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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.
Copyright:
2018

Book Details

Book Quality:
Publisher Quality
ISBN-13:
9783319964225
Related ISBNs:
9783319964201
Publisher:
Springer International Publishing
Date of Addition:
Copyrighted By:
Springer Nature Switzerland AG
Adult content:
No
Language:
English
Has Image Descriptions:
No
Categories:
Nonfiction, Computers and Internet, Earth Sciences, Mathematics and Statistics, Medicine, Sociology
Submitted By:
Bookshare Staff
Usage Restrictions:
This is a copyrighted book.

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