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Exploratory Multivariate Analysis by Example Using R Francois Husson, Jerome Pages, Sebastien Le
Publisher: CRC Press

Book Description: JSS JournalofStatisticalSoftware April 2011, Volume 40, Book Review 2. Through the examples in the book "Exploratory Multivariate Analysis by. Exploratory analysis and dimensionality reduction: principal component analysis, principal component and crimcoord displays, implementation in R. Exploratory Multivariate Analysis by Example Using R Francoi˘ s Husson, S ebastien L^e, J erome Pag es in the particular eld of statistics. The analysis of multivariate data requires the extension of standard univariate statistical and classification (use in medical diagnosis problems for example) are studied. Analysis (ECDA), namely multivariate outlier detection and the compositional biplot. 10.3 Multiple Regression: 10.4.2 Least Squares Estimation in the Multivariate Model , 339 .. Exploratory multivariate analysis in archaeology Multivariate archaeology: numerical approaches in Scandinavian archaeology Mike Fletcher,Gary R. Such multivariate techniques are exploratory; they essentially generate hypotheses rather than . The methods are illustrated at a small data example using the R package. Each chapter ends with a set of exercises. Exploratory multivariate analysis by example using R / François Husson, Sébastien Lê, Jérôme Pagès, CRC Press, 2011, 236 pp. A few examples of analyses for each case are as follows: 1. The book may be used as a text in a class on statistical graphics or exploratory data analysis, for example, or as a guide for the independent learner. The authors are both Fellows of the American Statistical Association Keywords » data analysis software - data visualization - direct manipulation - multivariate data - visual data mining.