Table of contents

  1. Front Matter
    Pages I-XVII
  2. Descriptive Techniques

    1. Front Matter
      Pages 1-1
    2. Wolfgang Karl Härdle, Léopold Simar
      Pages 3-46
  3. Multivariate Random Variables

    1. Front Matter
      Pages 47-47
    2. Wolfgang Karl Härdle, Léopold Simar
      Pages 49-71
    3. Wolfgang Karl Härdle, Léopold Simar
      Pages 73-106
    4. Wolfgang Karl Härdle, Léopold Simar
      Pages 107-165
    5. Wolfgang Karl Härdle, Léopold Simar
      Pages 167-181
    6. Wolfgang Karl Härdle, Léopold Simar
      Pages 183-192
    7. Wolfgang Karl Härdle, Léopold Simar
      Pages 193-226
  4. Multivariate Techniques

    1. Front Matter
      Pages 227-227
    2. Wolfgang Karl Härdle, Léopold Simar
      Pages 229-253
    3. Wolfgang Karl Härdle, Léopold Simar
      Pages 255-267
    4. Wolfgang Karl Härdle, Léopold Simar
      Pages 269-305
    5. Wolfgang Karl Härdle, Léopold Simar
      Pages 307-330
    6. Wolfgang Karl Härdle, Léopold Simar
      Pages 331-349
    7. Wolfgang Karl Härdle, Léopold Simar
      Pages 351-366
    8. Wolfgang Karl Härdle, Léopold Simar
      Pages 367-384
    9. Wolfgang Karl Härdle, Léopold Simar
      Pages 385-395
    10. Wolfgang Karl Härdle, Léopold Simar
      Pages 397-412

About this book

Introduction

Most of the observable phenomena in the empirical sciences are of a multivariate nature.  In financial studies, assets are observed simultaneously and their joint development is analysed to better understand general risk and to track indices.  In medicine recorded observations of subjects in different locations are the basis of reliable diagnoses and medication.  In quantitative marketing consumer preferences are collected in order to construct models of consumer behavior.  The underlying data structure of these and many other quantitative studies of applied sciences is multivariate.  Focusing on applications this book presents the tools and concepts of multivariate data analysis in a way that is understandable for non-mathematicians and practitioners who need to analyze statistical data.  The book surveys the basic principles of multivariate statistical data analysis and emphasizes both exploratory and inferential statistics.  All chapters have exercises that highlight applications in different fields.

The third edition of this book on Applied Multivariate Statistical Analysis offers the following new features

  • A new Chapter on Regression Models has been added
  • All numerical examples have been redone, updated and made reproducible in MATLAB or R, see www.quantlet.org for a repository of quantlets.

Keywords

Cluster Analysis Conjoint Measurement Analysis Discriminant Analysis Hypothesis Testing Multyvariate Analysis Projection Persuit Sliced Inverse Regression

Authors and affiliations

  • Wolfgang Karl Härdle
    • 1
  • Léopold Simar
    • 2
  1. 1.L.v.Bortkiewicz Chair of Statistics, C.A.S.E. Centre f. Appl. Stat. & Econ.Humboldt-Universität zu BerlinBerlinGermany
  2. 2.Inst. Statistics, Center of Operations Research &Katholieke Univeristeit LeuvenLeuvenBelgium

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-642-17229-8
  • Copyright Information Springer-Verlag Berlin Heidelberg 2012
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Mathematics and Statistics
  • Print ISBN 978-3-642-17228-1
  • Online ISBN 978-3-642-17229-8
  • About this book