TY  - BOOK
AU  - H�rdle,Wolfgang Karl
AU  - Simar,L�opold
ED  - SpringerLink (Online service)
TI  - Applied Multivariate Statistical Analysis
SN  - 9783662451717
AV  - QA276-280 
U1  - 330.015195 23
PY  - 2015///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg, Imprint: Springer
KW  - Statistics
KW  - Finance
KW  - Mathematical statistics
KW  - Economics
KW  - Statistics for Business/Economics/Mathematical Finance/Insurance
KW  - Quantitative Finance
KW  - Economic Theory
KW  - Statistical Theory and Methods
N1  - 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
N2  - 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 H�rdle, W. and Hlavka, Z., Multivariate Statistics: Exercises and Solutions. Springer Verlag, Heidelberg
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