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＜電子ブック＞
Analyzing Compositional Data with R / by K. Gerald van den Boogaart, Raimon Tolosana-Delgado
(Use R!. ISSN:21975744)

版	1st ed. 2013.
出版者	(Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer)
出版年	2013
本文言語	英語
大きさ	XV, 258 p. 62 illus., 20 illus. in color : online resource
著者標目	*van den Boogaart, K. Gerald author Tolosana-Delgado, Raimon author SpringerLink (Online service)
件　名	LCSH:Statistics  LCSH:Mathematical statistics -- Data processing  全ての件名で検索 LCSH:Geochemistry FREE:Statistical Theory and Methods FREE:Statistics and Computing FREE:Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences FREE:Geochemistry
一般注記	Introduction -- Fundamental Concepts of Compositional Data Analysis -- Distributions for Random Compositions -- Descriptive Analysis of Compositional Data -- Linear Models for Compositions -- Multivariate Statistics -- Zeroes, Missings and Outliers -- References -- Index.   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 to data visualization and model display issues. Many illustrated examples and code chunks guide the reader into their modeling and interpretation. And, though the book primarily serves as a reference guide for the R package “compositions,” it is also a general introductory text on Compositional Data Analysis. Awareness of their special characteristics spread in the Geosciences in the early sixties, but a strategy for properly dealing with them was not available until the works of Aitchison in the eighties. Since then, research has expanded our understanding of their theoretical principles and the potentials and limitations of their interpretation. This is the first comprehensive textbook addressing these issues, as well as their practical implications with regard to software. The book is intended for scientists interested in statistically analyzing their compositional data. The subject enjoys relatively broad awareness in the geosciences and environmental sciences, but the spectrum of recent applications also covers areas like medicine, official statistics, and economics. Readers should be familiar with basic univariate and multivariate statistics. Knowledge of R is recommended but not required, as the book is self-contained HTTP:URL=https://doi.org/10.1007/978-3-642-36809-7

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