Applied Multivariate Statistical Analysis

Focusing on high-dimensional applications, 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.

The fourth edition of this book on Applied Multivariate Statistical Analysis offers the following new features:

A new chapter on Variable Selection (Lasso, SCAD and Elastic Net)

All exercises are supplemented by R and MATLAB code that can be found on www.quantlet.de.

The practical exercises include solutions that can be found in Hardle, W. and Hlavka, Z., Multivariate Statistics: Exercises and Solutions. Springer Verlag, Heidelberg.

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Concentrandu-se pe aplicatii de inalta dimensiune, aceasta editie a 4-a prezinta instrumentele si conceptele utilizate in analiza datelor multivariate intr-un stil accesibil si non-matematicienilor si practicienilor. Acesta analizeaza principiile de baza si subliniaza atat statisticile exploratorii, cat si cele inferentiale; a fost adaugat si un nou capitol despre Selectia variabilelor (Lasso, SCAD si Elastic Net).