• Medientyp: E-Book
  • Titel: Applied Multivariate Statistical Analysis
  • Enthält: I Descriptive Techniques: Comparison of Batches.- II Multivariate Random Variables: A Short Excursion into Matrix AlgebraMoving to Higher Dimensions -- Multivariate Distributions -- Theory of the Multinormal -- Theory of Estimation -- Hypothesis Testing -- III Multivariate Techniques: Regression Models -- Variable Selection -- Decomposition of Data Matrices by Factors -- Principal Components Analysis -- Factor Analysis -- Cluster Analysis -- Discriminant Analysis -- Correspondence Analysis -- Canonical Correlation Analysis -- Multidimensional Scaling -- Conjoint Measurement Analysis -- Applications in Finance -- Computationally Intensive Techniques -- IV Appendix: Symbols and Notations -- Data.
  • Beteiligte: Härdle, Wolfgang Karl [VerfasserIn]; Simar, Léopold [Sonstige Person, Familie und Körperschaft]
  • Erschienen: Berlin, Heidelberg: Springer, 2015
  • Erschienen in: SpringerLink ; Bücher
  • Ausgabe: 4th ed. 2015
  • Umfang: Online-Ressource (XIII, 580 p. 221 illus., 83 illus. in color, online resource)
  • Sprache: Englisch
  • DOI: 10.1007/978-3-662-45171-7
  • ISBN: 9783662451717
  • Identifikator:
  • RVK-Notation: SK 830 : Statistische Entscheidungstheorie
  • Schlagwörter: Multivariate Analyse
    Multivariate Analyse
  • Entstehung:
  • Anmerkungen:
  • Beschreibung: 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