Applied Multivariate Statistical Analysis. 5th ed. 2019

種類:

電子ブック

責任表示:

by Wolfgang Karl Härdle, Léopold Simar

出版情報:

Cham : Springer International Publishing : Imprint: Springer, 2019

著者名:

• Härdle, Wolfgang Karl.
• Simar, Léopold.
• SpringerLink (Online service)

ISBN:

9783030260064 [3030260062]    

注記:

Part I Descriptive Techniques -- 1 Comparison of Batches -- Part 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 -- Part 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 -- Part IV Appendix -- A Symbols and Notations -- B Data -- Index -- References.
This textbook presents the tools and concepts used in multivariate data analysis in a style accessible for non-mathematicians and practitioners. All chapters include practical exercises that highlight applications in different multivariate data analysis fields, and all the examples involve high to ultra-high dimensions and represent a number of major fields in big data analysis. For this new edition, the book has been updated and extensively revised and now includes an extended chapter on cluster analysis. All solutions to the exercises are supplemented by R and MATLAB or SAS computer code and can be downloaded from the Quantlet platform. Practical exercises from this book and their solutions can also be found in the accompanying Springer book by W.K. Härdle and Z. Hlávka: Multivariate Statistics - Exercises and Solutions. The Quantlet platform, quantlet.de, quantlet.com, quantlet.org, is an integrated QuantNet environment consisting of different types of statistics-related documents and program codes. Its go

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