Ebook: 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 Härdle, W. and Hlavka, Z., Multivariate Statistics: Exercises and Solutions. Springer Verlag, Heidelberg.

---

Revised and updated fourth edition offers a broader range of material Offers a wide scope of methods and applications, making this a comprehensive treatment of the subject Includes a wealth of examples and exercises—ideal for students in economics and finance Quantlets in R and Matlab available online 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 Härdle, W. and Hlavka, Z., Multivariate Statistics: Exercises and Solutions. Springer Verlag, Heidelberg. Content Level » Graduate Keywords » Cluster Analysis - Conjoint Measurement Analysis - Discriminant Analysis - Elastic Net - Hypothesis Testing - Lasso - Multivariate Analysis - Projection Persuit - Sliced Inverse Regression Related subjects » Business, Economics & Finance - Economic Theory - Quantitative Finance - Statistical Theory and Methods