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Applied Multivariate Statistical Analysis

  • Wolfgang Karl Härdle
  • Léopold Simar

Table of contents

  1. Front Matter
    Pages i-xiii
  2. Descriptive Techniques

    1. Front Matter
      Pages 1-1
    2. Wolfgang Karl Härdle, Léopold Simar
      Pages 3-50
  3. Multivariate Random Variables

    1. Front Matter
      Pages 51-51
    2. Wolfgang Karl Härdle, Léopold Simar
      Pages 53-77
    3. Wolfgang Karl Härdle, Léopold Simar
      Pages 79-115
    4. Wolfgang Karl Härdle, Léopold Simar
      Pages 117-181
    5. Wolfgang Karl Härdle, Léopold Simar
      Pages 183-199
    6. Wolfgang Karl Härdle, Léopold Simar
      Pages 201-211
    7. Wolfgang Karl Härdle, Léopold Simar
      Pages 213-249
  4. Multivariate Techniques

    1. Front Matter
      Pages 251-251
    2. Wolfgang Karl Härdle, Léopold Simar
      Pages 253-280
    3. Wolfgang Karl Härdle, Léopold Simar
      Pages 281-304
    4. Wolfgang Karl Härdle, Léopold Simar
      Pages 305-318
    5. Wolfgang Karl Härdle, Léopold Simar
      Pages 319-358
    6. Wolfgang Karl Härdle, Léopold Simar
      Pages 359-384
    7. Wolfgang Karl Härdle, Léopold Simar
      Pages 385-405
    8. Wolfgang Karl Härdle, Léopold Simar
      Pages 407-424
    9. Wolfgang Karl Härdle, Léopold Simar
      Pages 425-442
    10. Wolfgang Karl Härdle, Léopold Simar
      Pages 443-454
    11. Wolfgang Karl Härdle, Léopold Simar
      Pages 455-472
    12. Wolfgang Karl Härdle, Léopold Simar
      Pages 473-486
    13. Wolfgang Karl Härdle, Léopold Simar
      Pages 487-499
    14. Wolfgang Karl Härdle, Léopold Simar
      Pages 501-554
  5. Appendix

    1. Front Matter
      Pages 555-555
    2. Wolfgang Karl Härdle, Léopold Simar
      Pages 557-560
    3. Wolfgang Karl Härdle, Léopold Simar
      Pages 561-571
  6. Back Matter
    Pages 573-580

About this book

Introduction

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.

Keywords

Cluster Analysis Conjoint Measurement Analysis Discriminant Analysis Elastic Net Hypothesis Testing Lasso Multivariate Analysis Projection Persuit Sliced Inverse Regression

Authors and affiliations

  • Wolfgang Karl Härdle
    • 1
  • Léopold Simar
    • 2
  1. 1.C.A.S.E. Centre f. Appl. Stat. & Econ. School of Business and EconomicsHumboldt-Universität zu BerlinBerlinGermany
  2. 2.Center of Operations Research & Econometrics (CORE)Katholieke Univeristeit Leuven Inst. StatisticsLeuvenBelgium

Bibliographic information