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150302 ||| eng |
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|a 9783662451717
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| 100 |
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|a Härdle, Wolfgang Karl
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| 245 |
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|a Applied Multivariate Statistical Analysis
|h Elektronische Ressource
|c by Wolfgang Karl Härdle, Léopold Simar
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| 250 |
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|a 4th ed. 2015
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| 260 |
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|a Berlin, Heidelberg
|b Springer Berlin Heidelberg
|c 2015, 2015
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| 300 |
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|a XIII, 580 p. 221 illus., 83 illus. in color
|b online resource
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| 505 |
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|a 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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| 653 |
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|a Statistical Theory and Methods
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| 653 |
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|a Mathematics in Business, Economics and Finance
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| 653 |
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|a Statistics
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| 653 |
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|a Statistics in Business, Management, Economics, Finance, Insurance
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| 653 |
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|a Quantitative Economics
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| 653 |
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|a Social sciences / Mathematics
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| 653 |
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|a Econometrics
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| 700 |
1 |
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|a Simar, Léopold
|e [author]
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| 041 |
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7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 028 |
5 |
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|a 10.1007/978-3-662-45171-7
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| 856 |
4 |
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|u https://doi.org/10.1007/978-3-662-45171-7?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
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|a 300.727
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| 520 |
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|a 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
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