Applied Multivariate Statistical Analysis
Business & Finance, Economics, Statistics, Nonfiction, Science & Nature, Mathematics, Applied
| Author: | Léopold Simar, Wolfgang Karl Härdle | ISBN: | 9783662451717 |
| Publisher: | Springer Berlin Heidelberg | Publication: | February 26, 2015 |
| Imprint: | Springer | Language: | English |
| Author: | Léopold Simar, Wolfgang Karl Härdle |
| ISBN: | 9783662451717 |
| Publisher: | Springer Berlin Heidelberg |
| Publication: | February 26, 2015 |
| Imprint: | Springer |
| Language: | English |
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. All chapters include practical exercises that highlight applications in different multivariate data analysis fields. All of the 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:
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A new chapter on Variable Selection (Lasso, SCAD and Elastic Net)
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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.
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. All chapters include practical exercises that highlight applications in different multivariate data analysis fields. All of the 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.
