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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 logarithms of ratios. This book explains how this transformation affects the analysis, results and interpretation of this very special type of data. All aspects of compositional data analysis are considered: visualization, modelling, dimension-reduction, clustering and variable selection, with many examples in the fields of food science, archaeology, sociology and biochemistry, and a final chapter containing a complete case study using fatty acid compositions in ecology. The applicability of these methods extends to other fields such as linguistics, geochemistry, marketing, economics and finance.R SoftwareThe R package easyCODA, which accompanies this book, can be downloaded from R-Forge as follows: install.packages and will be available on CRAN soon. Notice that the R packages ca and vegan also have to be installed (from CRAN in the usual way)
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This book reports on the latest advances in concepts and further developments of principal component analysis (PCA), addressing a number of open problems related to dimensional reduction techniques and their extensions in detail. Bringing together research results previously scattered throughout many scientific journals papers worldwide, the book presents them in a methodologically unified form. Offering vital insights into the subject matter in self-contained chapters that balance the theory and concrete applications, and especially focusing on open problems, it is essential reading for all researchers and practitioners with an interest in PCA.
Engineering. --- Pattern recognition. --- Computer mathematics. --- Computational intelligence. --- Biomedical engineering. --- Signal, Image and Speech Processing. --- Pattern Recognition. --- Computational Intelligence. --- Computational Mathematics and Numerical Analysis. --- Biomedical Engineering. --- Clinical engineering --- Medical engineering --- Bioengineering --- Biophysics --- Engineering --- Medicine --- Intelligence, Computational --- Artificial intelligence --- Soft computing --- Computer mathematics --- Discrete mathematics --- Electronic data processing --- Design perception --- Pattern recognition --- Form perception --- Perception --- Figure-ground perception --- Construction --- Industrial arts --- Technology --- Mathematics --- Principal components analysis. --- Analysis, Principal components --- Components analysis, Principal --- Correlation (Statistics) --- Factor analysis --- Optical pattern recognition. --- Computer science --- Biomedical Engineering and Bioengineering. --- Mathematics. --- Optical data processing --- Pattern perception --- Perceptrons --- Visual discrimination --- Signal processing. --- Image processing. --- Speech processing systems. --- Computational linguistics --- Electronic systems --- Information theory --- Modulation theory --- Oral communication --- Speech --- Telecommunication --- Singing voice synthesizers --- Pictorial data processing --- Picture processing --- Processing, Image --- Imaging systems --- Processing, Signal --- Information measurement --- Signal theory (Telecommunication)
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