Applied multivariate statistical analysis / Wolfgang Karl Hardle and Leopold Simar.
Publication details: Berlin : Springer-Verlag, 2015.Edition: 4th edDescription: xiii, 580 p. : illustrations (some colour) ; 24 cmISBN:- 9783662451700
- 000SA.07 23 H264
| Item type | Current library | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|
| Books | ISI Library, Kolkata | 000SA.07 H264 (Browse shelf(Opens below)) | Available | 136668 |
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| 000SA.07 D951 Principles of copula theory / | 000SA.07 El37 Joint modeling of longitudinal and time-to-event data / | 000SA.07 H112 Multivariate general linear models / | 000SA.07 H264 Applied multivariate statistical analysis / | 000SA.07 H286 Essence of multivariate thinking : basic themes and methods / | 000SA.07 H641 Modeling count data / | 000SA.07 H873 Theoretical foundations of functional data analysis, with an introduction to linear operators / |
Includes bibliographical references and index.
I Descriptive Techniques:
1. Comparison of Batches.-
II Multivariate Random Variables:
2. A Short Excursion into Matrix Algebra --
3. Moving to Higher Dimensions --
4. Multivariate Distributions --
5. Theory of the Multinormal --
6. Theory of Estimation --
7. Hypothesis Testing --
III Multivariate Techniques:
8. Regression Models --
9. Variable Selection --
10. Decomposition of Data Matrices by Factors --
11. Principal Components Analysis --
12. Factor Analysis --
13. Cluster Analysis --
14. Discriminant Analysis --
15. Correspondence Analysis --
16. Canonical Correlation Analysis --
17. Multidimensional Scaling --
18. Conjoint Measurement Analysis --
19. Applications in Finance --
20. Computationally Intensive Techniques --
IV Appendix:
21. Symbols and Notations --
22. Data --
References --
Index.
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.
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