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 goal is to promote reproducibility and offer a platform for sharing validated knowledge native to the social web. QuantNet and the corresponding data-driven document-based visualization allow readers to reproduce the tables, pictures and calculations presented in this Springer book.
Author(s): Wolfgang Karl Härdle, Léopold Simar
Publisher: Springer
Year: 2019
Language: English
Pages: 550
Tags: Statistical Theory And Methods
Front Matter ....Pages i-xii
Front Matter ....Pages 1-1
Comparison of Batches (Wolfgang Karl Härdle, Léopold Simar)....Pages 3-43
Front Matter ....Pages 45-45
A Short Excursion into Matrix Algebra (Wolfgang Karl Härdle, Léopold Simar)....Pages 47-69
Moving to Higher Dimensions (Wolfgang Karl Härdle, Léopold Simar)....Pages 71-105
Multivariate Distributions (Wolfgang Karl Härdle, Léopold Simar)....Pages 107-166
Theory of the Multinormal (Wolfgang Karl Härdle, Léopold Simar)....Pages 167-182
Theory of Estimation (Wolfgang Karl Härdle, Léopold Simar)....Pages 183-193
Hypothesis Testing (Wolfgang Karl Härdle, Léopold Simar)....Pages 195-229
Front Matter ....Pages 231-231
Regression Models (Wolfgang Karl Härdle, Léopold Simar)....Pages 233-259
Variable Selection (Wolfgang Karl Härdle, Léopold Simar)....Pages 261-283
Decomposition of Data Matrices by Factors (Wolfgang Karl Härdle, Léopold Simar)....Pages 285-297
Principal Components Analysis (Wolfgang Karl Härdle, Léopold Simar)....Pages 299-336
Factor Analysis (Wolfgang Karl Härdle, Léopold Simar)....Pages 337-361
Cluster Analysis (Wolfgang Karl Härdle, Léopold Simar)....Pages 363-393
Discriminant Analysis (Wolfgang Karl Härdle, Léopold Simar)....Pages 395-411
Correspondence Analysis (Wolfgang Karl Härdle, Léopold Simar)....Pages 413-430
Canonical Correlation Analysis (Wolfgang Karl Härdle, Léopold Simar)....Pages 431-442
Multidimensional Scaling (Wolfgang Karl Härdle, Léopold Simar)....Pages 443-459
Conjoint Measurement Analysis (Wolfgang Karl Härdle, Léopold Simar)....Pages 461-473
Applications in Finance (Wolfgang Karl Härdle, Léopold Simar)....Pages 475-486
Computationally Intensive Techniques (Wolfgang Karl Härdle, Léopold Simar)....Pages 487-539
Front Matter ....Pages 541-541
Symbols and Notations (Wolfgang Karl Härdle, Léopold Simar)....Pages 543-546
Data (Wolfgang Karl Härdle, Léopold Simar)....Pages 547-553
Back Matter ....Pages 555-558
