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＜電子ブック＞
Applied Multivariate Statistical Analysis / by Wolfgang Karl Härdle, Léopold Simar

版	4th ed. 2015.
出版者	(Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer)
出版年	2015
本文言語	英語
大きさ	XIII, 580 p. 221 illus., 83 illus. in color : online resource
著者標目	*Härdle, Wolfgang Karl author Simar, Léopold author SpringerLink (Online service)
件　名	LCSH:Statistics  LCSH:Social sciences -- Mathematics  全ての件名で検索 LCSH:Econometrics FREE:Statistics in Business, Management, Economics, Finance, Insurance FREE:Mathematics in Business, Economics and Finance FREE:Quantitative Economics FREE:Statistical Theory and Methods
一般注記	I Descriptive Techniques: Comparison of Batches -- II Multivariate Random Variables: A Short Excursion into Matrix Algebra -- Moving 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 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 HTTP:URL=https://doi.org/10.1007/978-3-662-45171-7

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