Modern multivariate statistical techniques von izenman alan (8 Ergebnisse)
Sprache: Englisch
Verlag: Springer, 2008
Serie: Springer Texts in Statistics, Buch 36 von 111. Buch 36 von 111 - Springer Texts in Statistics
- Hardcover
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hardcover. Zustand: Very Good.
Sprache: Englisch
Verlag: Springer, 2008
Serie: Springer Texts in Statistics, Buch 36 von 111. Buch 36 von 111 - Springer Texts in Statistics
- Hardcover
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Weitere BilderSprache: Englisch
Verlag: Springer, 2008
Serie: Springer Texts in Statistics, Buch 36 von 111. Buch 36 von 111 - Springer Texts in Statistics
- Hardcover
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Hardcover. Zustand: Sehr gut. 758 pp Spine slightly discolored, otherwise very well-preserved copy 377 Sprache: Englisch Gewicht in Gramm: 1339.
Sprache: Englisch
Verlag: Humana, 2016
Serie: Springer Texts in Statistics, Buch 36 von 111. Buch 36 von 111 - Springer Texts in Statistics
- Softcover
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Taschenbuch. Zustand: Neu. Modern Multivariate Statistical Techniques | Regression, Classification, and Manifold Learning | Alan J. Izenman | Taschenbuch | Springer Texts in Statistics | xxv | Englisch | 2016 | Humana | EAN 9781493938322 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelbe…rg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Sprache: Englisch
Verlag: Springer, Humana, 2016
Serie: Springer Texts in Statistics, Buch 36 von 111. Buch 36 von 111 - Springer Texts in Statistics
- Softcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Remarkable advances in computation and data storage and the ready availability of huge data sets have been the keys to the growth of the new disciplines of data mining and machine learning, while the enormous success of the Human Genome Project has o…pened up the field of bioinformatics. These exciting developments, which led to the introduction of many innovative statistical tools for high-dimensional data analysis, are described here in detail. The author takes a broad perspective; for the first time in a book on multivariate analysis, nonlinear methods are discussed in detail as well as linear methods. Techniques covered range from traditional multivariate methods, such as multiple regression, principal components, canonical variates, linear discriminant analysis, factor analysis, clustering, multidimensional scaling, and correspondence analysis, to the newer methods of density estimation, projection pursuit, neural networks, multivariate reduced-rank regression, nonlinear manifold learning, bagging, boosting, random forests, independent component analysis, support vector machines, and classification and regression trees. Another unique feature of this book is the discussion of database management systems.This book is appropriate for advanced undergraduate students, graduate students, and researchers in statistics, computer science, artificial intelligence, psychology, cognitive sciences, business, medicine, bioinformatics, and engineering. Familiarity with multivariable calculus, linear algebra, and probability and statistics is required. The book presents a carefully-integrated mixture of theory and applications, and of classical and modern multivariate statistical techniques, including Bayesian methods. There are over 60 interesting data sets used as examples in the book, over 200 exercises, and many color illustrations and photographs.
Sprache: Englisch
Verlag: Springer, Humana, 2008
Serie: Springer Texts in Statistics, Buch 36 von 111. Buch 36 von 111 - Springer Texts in Statistics
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Remarkable advances in computation and data storage and the ready availability of huge data sets have been the keys to the growth of the new disciplines of data mining and machine learning, while the enormous success of the Human Genome Project has opened u…p the field of bioinformatics. These exciting developments, which led to the introduction of many innovative statistical tools for high-dimensional data analysis, are described here in detail. The author takes a broad perspective; for the first time in a book on multivariate analysis, nonlinear methods are discussed in detail as well as linear methods. Techniques covered range from traditional multivariate methods, such as multiple regression, principal components, canonical variates, linear discriminant analysis, factor analysis, clustering, multidimensional scaling, and correspondence analysis, to the newer methods of density estimation, projection pursuit, neural networks, multivariate reduced-rank regression, nonlinear manifold learning, bagging, boosting, random forests, independent component analysis, support vector machines, and classification and regression trees. Another unique feature of this book is the discussion of database management systems.This book is appropriate for advanced undergraduate students, graduate students, and researchers in statistics, computer science, artificial intelligence, psychology, cognitive sciences, business, medicine, bioinformatics, and engineering. Familiarity with multivariable calculus, linear algebra, and probability and statistics is required. The book presents a carefully-integrated mixture of theory and applications, and of classical and modern multivariate statistical techniques, including Bayesian methods. There are over 60 interesting data sets used as examples in the book, over 200 exercises, and many color illustrations and photographs.
Sprache: Englisch
Verlag: Springer, 2008
Serie: Springer Texts in Statistics, Buch 36 von 111. Buch 36 von 111 - Springer Texts in Statistics
- Hardcover
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Zustand: Very Good. Item in very good condition! Textbooks may not include supplemental items i.e. CDs, access codes etc.
Sprache: Englisch
Verlag: Springer Verlag, 2008
Serie: Springer Texts in Statistics, Buch 36 von 111. Buch 36 von 111 - Springer Texts in Statistics
- Hardcover
Anbieter: Revaluation Books, Exeter, Vereinigtes KönigreichRevaluation Books
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Hardcover. Zustand: Brand New. 1st edition. 734 pages. 9.75x6.50x1.50 inches. In Stock.
