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#### Constrained Principal Component Analysis and Related Techniques

CRC Press 2016; US$ 94.95In multivariate data analysis, regression techniques predict one set of variables from another while principal component analysis (PCA) finds a subspace of minimal dimensionality that captures the largest variability in the data. How can regression analysis and PCA be combined in a beneficial way? Why and when is it a good idea to combine... more...

#### Correspondence Analysis

Wiley 2014; US$ 109.00A comprehensive overview of the internationalisation of correspondence analysis Correspondence Analysis: Theory, Practice and New Strategies examines the key issues of correspondence analysis, and discusses the new advances that have been made over the last 20 years. The main focus of this book is to provide a comprehensive discussion of some... more...

#### Elements of Dual Scaling

Taylor and Francis 2014; US$ 54.95Quantification methodology of categorical data is a popular topic in many branches of science. Most books, however, are either too advanced for those who need it, or too elementary to gain insight into its potential. This book fills the gap between these extremes, and provides specialists with an easy and comprehensive reference, and others with a... more...

#### Factor Analysis

Taylor and Francis 2013; US$ 78.95First published in 1993. Routledge is an imprint of Taylor & Francis, an informa company. more...

#### Factor Analysis

Taylor and Francis 2013; US$ 90.00Comprehensive and comprehensible, this classic covers the basic and advanced topics essential for using factor analysis as a scientific tool in psychology, education, sociology, and related areas. Emphasizing the usefulness of the techniques, it presents sufficient mathematical background for understanding and sufficient discussion of applications... more...

#### Factor Analysis at 100

Taylor and Francis 2012; US$ 56.95Factor analysis is one of the success stories of statistics in the social sciences. The reason for its wide appeal is that it provides a way to investigate latent variables, the fundamental traits and concepts in the study of individual differences. Because of its importance, a conference was held to mark the centennial of the publication of Charles... more...

#### Statistical Factor Analysis and Related Methods

Wiley 2009; US$ 160.00Statistical Factor Analysis and Related Methods Theory and Applications In bridging the gap between the mathematical and statistical theory of factor analysis, this new work represents the first unified treatment of the theory and practice of factor analysis and latent variable models. It focuses on such areas as: * The classical principal components... more...

#### Principal Manifolds for Data Visualization and Dimension Reduction

Springer Berlin Heidelberg 2007; Not AvailableIn 1901, Karl Pearson invented Principal Component Analysis (PCA). Since then, PCA serves as a prototype for many other tools of data analysis, visualization and dimension reduction: Independent Component Analysis (ICA), Multidimensional Scaling (MDS), Nonlinear PCA (NLPCA), Self Organizing Maps (SOM), etc. The book starts with the quote of the classical... more...

#### Correspondence Analysis in Practice, Second Edition

CRC Press 2007; US$ 109.95Drawing on the author's experience in social and environmental research, Correspondence Analysis in Practice, Second Edition shows how the versatile method of correspondence analysis (CA) can be used for data visualization in a wide variety of situations. This completely revised, up-to-date edition features a didactic approach with self-contained... more...

#### Multiple Correspondence Analysis and Related Methods

CRC Press 2006; US$ 154.95As a generalization of simple correspondence analysis, multiple correspondence analysis (MCA) is a powerful technique for handling larger, more complex datasets, including the high-dimensional categorical data often encountered in the social sciences, marketing, health economics, and biomedical research. Until now, however, the literature on the subject... more...