TY - GEN AU - Hardle,Wolfgang Karl AU - Simar,Leopold TI - Applied multivariate statistical analysis SN - 9783662451700 U1 - 000SA.07 23 PY - 2015/// CY - Berlin PB - Springer-Verlag KW - Multivariate Analysis KW - Statistical data Interpretation. N1 - Includes bibliographical references and index; I Descriptive Techniques: 1. Comparison of Batches.- II Multivariate Random Variables: 2. A Short Excursion into Matrix Algebra -- 3. Moving to Higher Dimensions -- 4. Multivariate Distributions -- 5. Theory of the Multinormal -- 6. Theory of Estimation -- 7. Hypothesis Testing -- III Multivariate Techniques: 8. Regression Models -- 9. Variable Selection -- 10. Decomposition of Data Matrices by Factors -- 11. Principal Components Analysis -- 12. Factor Analysis -- 13. Cluster Analysis -- 14. Discriminant Analysis -- 15. Correspondence Analysis -- 16. Canonical Correlation Analysis -- 17. Multidimensional Scaling -- 18. Conjoint Measurement Analysis -- 19. Applications in Finance -- 20. Computationally Intensive Techniques -- IV Appendix: 21. Symbols and Notations -- 22. Data -- References -- Index N2 - This 4th edition presents the tools and concepts used in multivariate data analysis in a style that is also accessible for non-mathematicians and practitioners. It surveys the basic principles and emphasizes both exploratory and inferential statistics; a new chapter on Variable Selection (Lasso, SCAD and Elastic Net) has also been added. All chapters include practical exercises that highlight applications in different multivariate data analysis fields: in quantitative financial studies, where the joint dynamics of assets are observed; in medicine, where recorded observations of subjects in different locations form the basis for reliable diagnoses and medication; and in quantitative marketing, where consumers’ preferences are collected in order to construct models of consumer behavior. All of these examples involve high to ultra-high dimensions and represent a number of major fields in big data analysis ER -