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.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
From the reviews:
"The authors’ intention is to present multivariate data analysis in a way that is understandable to non-mathematicians and practitioners who are confronted by statistical data analysis ... . The book has a friendly yet rigorous style. All methods are demonstrated through numerous real examples. Mathematical results are clearly stated ... . All chapters contain numerous theoretical and practical exercises. ... it can be said that the authors have fully attained their goals." (Ricardo Maronna, Statistical Papers, Vol. 46 (1), 2005)
"This textbook gives a broad and modern introduction to statistics for multivariate data. A bunch of interesting examples is used to illustrate the techniques. ... All chapters are finished by memorable summaries subsuming the main results and a couple of exercises. The mathematical background and derivations are concise, while practical aspects like computation and visualization are stressed using detailed examples. ... I consider the book to be an excellent starting point for everybody interested in learning about statistical methods for multivariable data sets." (R. Fried, Metrika, 2006)
"The mathematics and statistical theory is at the graduate statistics level, and at that level, this book is superb. ... Many of the applications ... are packed with graphical presentations and are very informative and interesting to read. The exercises would be acceptable for classroom purposes. ... it would serve well as a reference to a ‘mathematically mature’ person already familiar with multivariate methods. The e-book version makes the work particularly valuable as a reference." (Charles E. Heckler, Technometrics, Vol. 47 (4), 2005)
"The book contains a state of the art presentation of the tools and concepts of multivariate data analysis with a strong focus on applications. ... It is an attractive blend of theory and practice with a wide range of examples and 228 exercises. All data sets used in the book can be downloaded and a downloadable online version offers interactive exercises and data analysis." (T. Postelnicu, Zentralblatt MATH, Vol. 1028, 2005)
"As the title of the book indicates this volume is particularly directed towards a readership that is interested in practical help when facing multivariate statistical problems. ... Moreover, the many examples accompanying the presentation of the different methods cover various areas of empirical research. ... It concludes with an appendix where we find all data sets used for the various real data examples. Each section provides a sample of exercises. ... particular feature of this book is that it belongs to the Springer e-books series." (Stefan Sperlich, Statistical Software Newsletter, 2004)
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: Decomposition of Data Matrices by Factors; Principal Components Analysis; Factor Analysis; Cluster Analysis; Discriminate Analysis.- Correspondence Analysis.- Canonical Correlation Analysis.- Multidimensional Scaling.- Conjoint Measurement Analysis.- Application in Finance.- Highly Interactive, Computationally Intensive Techniques.- A: Symbols and Notations.- B: Data.- Bibliography.- Index.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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Da: books4less (Versandantiquariat Petra Gros GmbH & Co. KG), Welling, Germania
Broschiert. Condizione: Gut. 486 Seiten Der Erhaltungszustand des hier angebotenen Werks ist trotz seiner Bibliotheksnutzung sehr sauber. Es befindet sich neben dem Rückenschild lediglich ein Bibliotheksstempel im Buch; ordnungsgemäß entwidmet. In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 700. Codice articolo 1696954
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