03633nam 2200601 a 450 991073940610332120200520144314.03-642-36809-310.1007/978-3-642-36809-7(CKB)2670000000403423(EBL)1317691(OCoLC)854976127(SSID)ssj0000962491(PQKBManifestationID)11491865(PQKBTitleCode)TC0000962491(PQKBWorkID)10969734(PQKB)11178315(DE-He213)978-3-642-36809-7(MiAaPQ)EBC1317691(PPN)172426030(EXLCZ)99267000000040342320130510d2013 uy 0engur|n|---|||||txtccrAnalyzing compositional data with R /Gerald van den Boogaart1st ed. 2013.New York Springer20131 online resource (269 p.)UseR!Description based upon print version of record.3-642-36808-5 Includes bibliographical references and index.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.Use R!,2197-5736Multivariate analysisCorrelation (Statistics)R (Computer program language)Multivariate analysis.Correlation (Statistics)R (Computer program language)005.55Boogaart Gerald Van den1759907MiAaPQMiAaPQMiAaPQBOOK9910739406103321Analyzing compositional data with R4198582UNINA