Advances In Compositional Data Analysis
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Advances In Compositional Data Analysis
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Author : Peter Filzmoser
language : en
Publisher: Springer Nature
Release Date : 2021-06-01
Advances In Compositional Data Analysis written by Peter Filzmoser and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-01 with Mathematics categories.
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 scientific disciplines and includes references to the latest software solutions available for compositional data analysis, thus providing a valuable and up-to-date guide for researchers and practitioners working with compositional data. Featuring selected contributions by leading experts in the field, the book is dedicated to Vera Pawlowsky-Glahn on the occasion of her 70th birthday.
Compositional Data Analysis
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Author : Vera Pawlowsky-Glahn
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-19
Compositional Data Analysis written by Vera Pawlowsky-Glahn and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-19 with Mathematics categories.
It is difficult to imagine that the statistical analysis of compositional data has been a major issue of concern for more than 100 years. It is even more difficult to realize that so many statisticians and users of statistics are unaware of the particular problems affecting compositional data, as well as their solutions. The issue of ``spurious correlation'', as the situation was phrased by Karl Pearson back in 1897, affects all data that measures parts of some whole, such as percentages, proportions, ppm and ppb. Such measurements are present in all fields of science, ranging from geology, biology, environmental sciences, forensic sciences, medicine and hydrology. This book presents the history and development of compositional data analysis along with Aitchison's log-ratio approach. Compositional Data Analysis describes the state of the art both in theoretical fields as well as applications in the different fields of science. Key Features: Reflects the state-of-the-art in compositional data analysis. Gives an overview of the historical development of compositional data analysis, as well as basic concepts and procedures. Looks at advances in algebra and calculus on the simplex. Presents applications in different fields of science, including, genomics, ecology, biology, geochemistry, planetology, chemistry and economics. Explores connections to correspondence analysis and the Dirichlet distribution. Presents a summary of three available software packages for compositional data analysis. Supported by an accompanying website featuring R code. Applied scientists working on compositional data analysis in any field of science, both in academia and professionals will benefit from this book, along with graduate students in any field of science working with compositional data.
Modeling And Analysis Of Compositional Data
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Author : Vera Pawlowsky-Glahn
language : en
Publisher: John Wiley & Sons
Release Date : 2015-02-17
Modeling And Analysis Of Compositional Data written by Vera Pawlowsky-Glahn and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-17 with Mathematics categories.
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 methodologies along with exercises at the end of each chapter to improve understanding, as well as data and a solutions manual which is available on an accompanying website. Complementing Pawlowsky-Glahn’s earlier collective text that provides an overview of the state-of-the-art in this field, Modeling and Analysis of Compositional Data fills a gap in the literature for a much-needed manual for teaching, self learning or consulting.
Analyzing Compositional Data With R
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Author : K. Gerald Van Den Boogaart
language : en
Publisher:
Release Date : 2013-07-31
Analyzing Compositional Data With R written by K. Gerald Van Den Boogaart and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-31 with categories.
Compositional Data Analysis
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Author : Josep Antoni Martín-Fernández
language : en
Publisher: Springer
Release Date : 2016-11-19
Compositional Data Analysis written by Josep Antoni Martín-Fernández and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-19 with Mathematics categories.
The authoritative contributions gathered in this volume reflect the state of the art in compositional data analysis (CoDa). The respective chapters cover all aspects of CoDa, ranging from mathematical theory, statistical methods and techniques to its broad range of applications in geochemistry, the life sciences and other disciplines. The selected and peer-reviewed papers were originally presented at the 6th International Workshop on Compositional Data Analysis, CoDaWork 2015, held in L’Escala (Girona), Spain. Compositional data is defined as vectors of positive components and constant sum, and, more generally, all those vectors representing parts of a whole which only carry relative information. Examples of compositional data can be found in many different fields such as geology, chemistry, economics, medicine, ecology and sociology. As most of the classical statistical techniques are incoherent on compositions, in the 1980s John Aitchison proposed the log-ratio approach to CoDa. This became the foundation of modern CoDa, which is now based on a specific geometric structure for the simplex, an appropriate representation of the sample space of compositional data. The International Workshops on Compositional Data Analysis offer a vital discussion forum for researchers and practitioners concerned with the statistical treatment and modelling of compositional data or other constrained data sets and the interpretation of models and their applications. The goal of the workshops is to summarize and share recent developments, and to identify important lines of future research.
Advances In Contemporary Statistics And Econometrics
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Author : Abdelaati Daouia
language : en
Publisher: Springer Nature
Release Date : 2021-06-14
Advances In Contemporary Statistics And Econometrics written by Abdelaati Daouia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-14 with Mathematics categories.
This book presents a unique collection of contributions on modern topics in statistics and econometrics, written by leading experts in the respective disciplines and their intersections. It addresses nonparametric statistics and econometrics, quantiles and expectiles, and advanced methods for complex data, including spatial and compositional data, as well as tools for empirical studies in economics and the social sciences. The book was written in honor of Christine Thomas-Agnan on the occasion of her 65th birthday. Given its scope, it will appeal to researchers and PhD students in statistics and econometrics alike who are interested in the latest developments in their field.
Compositional Data Analysis In Practice
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Author : Michael Greenacre
language : en
Publisher: CRC Press
Release Date : 2018-07-17
Compositional Data Analysis In Practice written by Michael Greenacre and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-17 with Business & Economics categories.
Compositional data are quantitative descriptions of the parts of some whole, conveying exclusively relative information. Examples are found in various fields, including geology, medicine, chemistry, agriculture, economics, social science, etc. This concise book presents a very applied introduction to compositional data analysis, focussing on the use of R for analysis. It includes lots of real examples, code snippets, and colour figures, to illustrate the methods.
Applied Compositional Data Analysis
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Author : Peter Filzmoser
language : en
Publisher: Springer
Release Date : 2018-11-03
Applied Compositional Data Analysis written by Peter Filzmoser and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-03 with Mathematics categories.
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.
Data Analysis Classification And Related Methods
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Author : Henk A.L. Kiers
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Data Analysis Classification And Related Methods written by Henk A.L. Kiers and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
This volume contains a selection of papers presented at the Seven~h Confer ence of the International Federation of Classification Societies (IFCS-2000), which was held in Namur, Belgium, July 11-14,2000. From the originally sub mitted papers, a careful review process involving two reviewers per paper, led to the selection of 65 papers that were considered suitable for publication in this book. The present book contains original research contributions, innovative ap plications and overview papers in various fields within data analysis, classifi cation, and related methods. Given the fast publication process, the research results are still up-to-date and coincide with their actual presentation at the IFCS-2000 conference. The topics captured are: • Cluster analysis • Comparison of clusterings • Fuzzy clustering • Discriminant analysis • Mixture models • Analysis of relationships data • Symbolic data analysis • Regression trees • Data mining and neural networks • Pattern recognition • Multivariate data analysis • Robust data analysis • Data science and sampling The IFCS (International Federation of Classification Societies) The IFCS promotes the dissemination of technical and scientific information data analysis, classification, related methods, and their applica concerning tions.
Robust And Multivariate Statistical Methods
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Author : Mengxi Yi
language : en
Publisher: Springer Nature
Release Date : 2023-04-19
Robust And Multivariate Statistical Methods written by Mengxi Yi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-19 with Mathematics categories.
This book presents recent developments in multivariate and robust statistical methods. Featuring contributions by leading experts in the field it covers various topics, including multivariate and high-dimensional methods, time series, graphical models, robust estimation, supervised learning and normal extremes. It will appeal to statistics and data science researchers, PhD students and practitioners who are interested in modern multivariate and robust statistics. The book is dedicated to David E. Tyler on the occasion of his pending retirement and also includes a review contribution on the popular Tyler’s shape matrix.