Multivariate statistics : exercises and solutions /

Multivariate statistics : exercises and solutions /

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Bibliographic Details
Author / Creator:Härdle, Wolfgang, author.
Edition:Second edition.
Imprint:Heidelberg : Springer, 2015.
Description:1 online resource (xxiv, 362 pages) : illustrations (some color)
Language:English
Series:Online access with purchase: Springer (t)
Subject:
Multivariate analysis.
Multivariate analysis.
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11094398
Hidden Bibliographic Details
Other authors / contributors:Hlávka, Z. (Zdeněk), author.
ISBN:9783642360053
364236005X
3642360041
9783642360046
9783642360046
Notes:Includes bibliographical references and index.
Online resource; title from PDF title page (SpringerLink, viewed June 10, 2015).
Summary:The authors present tools and concepts of multivariate data analysis by means of exercises and their solutions. The first part is devoted to graphical techniques. The second part deals with multivariate random variables and presents the derivation of estimators and tests for various practical situations. The last part introduces a wide variety of exercises in applied multivariate data analysis. The book demonstrates the application of simple calculus and basic multivariate methods in real life situations. It contains altogether more than 250 solved exercises which can assist a university teacher in setting up a modern multivariate analysis course. All computer-based exercises are available in the R language. All R codes and data sets may be downloaded via the quantlet download center www.quantlet.org or via the Springer webpage. For interactive display of low-dimensional projections of a multivariate data set, we recommend GGobi.
Other form:Printed edition: 9783642360046
Standard no.:10.1007/978-3-642-36005-3
Table of Contents:
  • Part I Descriptive Techniques: Comparison of Batches
  • Part II Multivariate Random Variables: A Short Excursion into Matrix Algebra
  • Moving to Higher
  • Multivariate
  • Theory of the Multinormal
  • Theory of Estimation
  • Part III Multivariate Techniques: Regression Models
  • Variable Selection
  • Decomposition of Data Matrices by Factors
  • Principal Component Analysis
  • Factor Analysis
  • Cluster Analysis
  • Discriminant Analysis
  • Correspondence Analysis
  • Canonical Correlation Analysis
  • Multidimensional Scaling
  • Conjoint Measurement Analysis
  • Applications in Finance
  • Highly Interactive, Computationally Intensive Techniques
  • Data Sets
  • References
  • Index.

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