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Applied multivariate statistical ana...
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Hardle, Wolfgang Karl.
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Applied multivariate statistical analysis
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Applied multivariate statistical analysis/ by Wolfgang Karl Hardle, Leopold Simar.
作者:
Hardle, Wolfgang Karl.
其他作者:
Simar, Leopold.
出版者:
Berlin, Heidelberg :Springer Berlin Heidelberg : : 2015.,
面頁冊數:
xiii, 580 p. :ill. (some col.), digital ;24 cm.
內容註:
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.
Contained By:
Springer eBooks
標題:
Multivariate analysis. -
電子資源:
http://dx.doi.org/10.1007/978-3-662-45171-7
ISBN:
9783662451717 (electronic bk.)
Applied multivariate statistical analysis
Hardle, Wolfgang Karl.
Applied multivariate statistical analysis
[electronic resource] /by Wolfgang Karl Hardle, Leopold Simar. - 4th ed. - Berlin, Heidelberg :Springer Berlin Heidelberg :2015. - xiii, 580 p. :ill. (some col.), digital ;24 cm.
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 Hardle, W. and Hlavka, Z., Multivariate Statistics: Exercises and Solutions. Springer Verlag, Heidelberg.
ISBN: 9783662451717 (electronic bk.)
Standard No.: 10.1007/978-3-662-45171-7doiSubjects--Topical Terms:
517467
Multivariate analysis.
LC Class. No.: QA278
Dewey Class. No.: 519.535
Applied multivariate statistical analysis
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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.
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