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Applied Compositional Data Analysis

Applied Compositional Data Analysis
Author: Peter Filzmoser
Publisher: Springer
ISBN: 3319964224
Size: 38.76 MB
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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.
Applied Compositional Data Analysis
Language: en
Pages: 280
Authors: Peter Filzmoser, Karel Hron, Matthias Templ
Categories: Mathematics
Type: BOOK - Published: 2018-11-03 - Publisher: Springer
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
Compositional Data Analysis
Language: en
Pages: 378
Authors: Vera Pawlowsky-Glahn, Antonella Buccianti
Categories: Mathematics
Type: BOOK - Published: 2011-09-19 - Publisher: John Wiley & Sons
Compositional Data Analysis: Theory and Applications Edited by Vera Pawlowsky-Glahn, Department of Computer Science and Applied Mathematics, University of Girona, Spain. Antonella Buccianti, Department of Earth Sciences, University of Florence, Italy It is difficult to imagine that the statistical analysis of compositional data has been a major issue of concern
The Statistical Analysis of Compositional Data
Language: en
Pages: 416
Authors: J. Aitchison, John W. Aitchison
Categories: Mathematics
Type: BOOK - Published: 1986-08-21 - Publisher: Springer
As long ago as 1897 Karl Pearson, in a now classic paper on spurious correlation, first pointed out dangers that may befall the analyst who attempts to interpret correlations between ratios whose numerators and denominators contain common parts. He thus implied that the analysis of compositional data, with its concentration
Compositional Data Analysis in Practice
Language: en
Pages: 120
Authors: Michael Greenacre
Categories: Business & Economics
Type: BOOK - Published: 2018-07-17 - Publisher: CRC Press
Compositional Data Analysis in Practice is a user-oriented practical guide to the analysis of data with the property of a constant sum, for example percentages adding up to 100%. Compositional data can give misleading results if regular statistical methods are applied, and are best analysed by first transforming them to
Modeling and Analysis of Compositional Data
Language: en
Pages: 272
Authors: Vera Pawlowsky-Glahn, Juan José Egozcue, Raimon Tolosana-Delgado
Categories: Mathematics
Type: BOOK - Published: 2015-03-30 - Publisher: John Wiley & Sons
Modeling and Analysis of Compositional Data presents a practical and comprehensive introduction to the analysis of compositional data along with numerous examples to illustrate both theory and application of each method. Based upon short courses delivered by the authors, it provides a complete and current compendium of fundamental to advanced
Analyzing Compositional Data with R
Language: en
Pages: 258
Authors: K. Gerald van den Boogaart, Raimon Tolosana-Delgado
Categories: Mathematics
Type: BOOK - Published: 2013-06-29 - Publisher: Springer Science & Business Media
This book presents the statistical analysis of compositional data sets, i.e., data in percentages, proportions, concentrations, etc. The subject is covered from its grounding principles to the practical use in descriptive exploratory analysis, robust linear models and advanced multivariate statistical methods, including zeros and missing values, and paying special attention
Advances in Compositional Data Analysis
Language: en
Pages: 404
Authors: Peter Filzmoser, Karel Hron, Josep Antoni Martín-Fernández, Javier Palarea-Albaladejo
Categories: Mathematics
Type: BOOK - Published: 2021-06-01 - Publisher: Springer Nature
This book presents modern methods and real-world applications of compositional data analysis. It covers a wide variety of topics, ranging from an updated presentation of basic concepts and ideas in compositional data analysis to recent advances in the context of complex data structures. Further, it illustrates real-world applications in numerous
Compositional Data Analysis in the Geosciences
Language: en
Pages: 212
Authors: Antonella Buccianti, G. Mateu-Figueras, Vera Pawlowsky-Glahn
Categories: Science
Type: BOOK - Published: 2006 - Publisher: Geological Society of London
Since Karl Pearson wrote his paper on spurious correlation in 1897, a lot has been said about the statistical analysis of compositional data, mainly by geologists such as Felix Chayes. The solution appeared in the 1980s, when John Aitchison proposed to use Iogratios. Since then, the approach has seen a
Comprehensive Chemometrics
Language: en
Pages: 2944
Authors: Steven Brown, Roma Tauler, Beata Walczak
Categories: Science
Type: BOOK - Published: 2020-05-26 - Publisher: Elsevier
Comprehensive Chemometrics, Second Edition features expanded and updated coverage, along with new content that covers advances in the field since the previous edition published in 2009. Subject of note include updates in the fields of multidimensional and megavariate data analysis, omics data analysis, big chemical and biochemical data analysis, data
New Developments in Statistical Disclosure Controland Imputation
Language: en
Pages: 264
Authors: Matthias Templ
Categories: Science
Type: BOOK - Published: 2009 - Publisher: Sudwestdeutscher Verlag Fur Hochschulschriften AG
The aim of statistical disclosure control is to keep up the required statistical privacy while making data available to the researchers. This can be achieved with the help of minimal modifications of the data without changing the multivariate data structure. In this book the well-developed R package sdc- Micro is