Applied Multivariate Statistical Analysis

Presenting the tools and concepts of multivariate data analysis in a way that is understandable for non-mathematicians, this third edition includes new features such as a chapter on regression models. All the numerical examples are reproduced in MATLAB or R.

The third edition of this book on Applied Multivariate Statistical Analysis offers the following new features A new Chapter on Regression Models has been addedAll numerical examples have been redone, updated and made reproducible in MATLAB or R, see www.quantlet.org for a repository of quantlets.

I. Descriptive Techniques: Comparison of Batches.- II. Multivariate Random Variables: A Short Excursion into Matrix Algebra.- Moving to Higher Dimensions.- Multivariate Distributions.- Theory of the Multinormal.- Theory of Estimation.- Hypothesis Testing.-
III. Multivariate Techniques: Regression Models.-
Decomposition of Data Matrices by Factors.- Principal Components Analysis.-
Factor Analysis.- Cluster Analysis.-
Discriminant Analysis.- Correspondence Analysis.- Canonical Correlation Analysis.- Multidimensional Scaling.- Conjoint Measurement Analysis.- Applications in Finance.- Computationally Intensive Techniques.- IV. Appendix.- Bibliography.- Index