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A First Course in Multivariate Statistics Bernard Flury Author
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ISBN: 9781441931139

A comprehensive and self-contained introduction to the field, carefully balancing mathematical theory and practical applications. It starts at an elementary level, developing concepts of … More...

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Flury, Bernard:

A First Course in Multivariate Statistics - Paperback

2010, ISBN: 1441931139

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Softcover reprint of hardcover 1st ed. 1997 Kartoniert / Broschiert Wahrscheinlichkeitsrechnung und Statistik, Randomvariable; Resampling; classification; expectation¿maximizationalgori… More...

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A First Course in Multivariate Statistics (Springer Texts in Statistics) - Flury, Bernard
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Flury, Bernard:
A First Course in Multivariate Statistics (Springer Texts in Statistics) - Paperback

2010

ISBN: 9781441931139

Springer, Taschenbuch, Auflage: Softcover reprint of hardcover 1st ed. 1997, 732 Seiten, Publiziert: 2010-11-24T00:00:01Z, Produktgruppe: Buch, 3.44 kg, Statistik, Naturwissenschaft & Mat… More...

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A First Course in Multivariate Statistics (Springer Texts in Statistics) - Flury, Bernard
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Flury, Bernard:
A First Course in Multivariate Statistics (Springer Texts in Statistics) - Paperback

2010, ISBN: 9781441931139

Springer, Taschenbuch, Auflage: Softcover reprint of hardcover 1st ed. 1997, 732 Seiten, Publiziert: 2010-11-24T00:00:01Z, Produktgruppe: Buch, 3.44 kg, Statistik, Naturwissenschaft & Mat… More...

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A First Course in Multivariate Statistics - Bernard Flury
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Bernard Flury:
A First Course in Multivariate Statistics - Paperback

2010, ISBN: 9781441931139

Buch, Softcover, Softcover reprint of hardcover 1st ed. 1997, [PU: Springer-Verlag New York Inc.], Springer-Verlag New York Inc., 2010

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A First Course in Multivariate Statistics Bernard Flury Author
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ISBN:

1441931139


A comprehensive and self-contained introduction to the field, carefully balancing mathematical theory and practical applications. It starts at an elementary level, developing concepts of multivariate distributions from first principles. After a chapter on the multivariate normal distribution reviewing the classical parametric theory, methods of estimation are explored using the plug-in principles as well as maximum likelihood. Two chapters on discrimination and classification, including logistic regression, form the core of the book, followed by methods of testing hypotheses developed from heuristic principles, likelihood ratio tests and permutation tests. Finally, the powerful self-consistency principle is used to introduce principal components as a method of approximation, rounded off by a chapter on finite mixture analysis.

Details of the book - A First Course in Multivariate Statistics Bernard Flury Author


EAN (ISBN-13): 9781441931139
ISBN (ISBN-10): 1441931139
Hardcover
Paperback
Publishing year: 2010
Publisher: Springer New York Core >1 >T
732 Pages
Weight: 1,339 kg
Language: eng/Englisch

Book in our database since 2010-02-23T08:34:50+00:00 (London)
Detail page last modified on 2024-01-09T15:25:32+00:00 (London)
ISBN/EAN: 1441931139

ISBN - alternate spelling:
1-4419-3113-9, 978-1-4419-3113-9
Alternate spelling and related search-keywords:
Book author: flury, flür
Book title: course, using multivariate statistics

Information from Publisher

Author: Bernard Flury
Title: Springer Texts in Statistics; A First Course in Multivariate Statistics
Publisher: Springer; Springer US
715 Pages
Publishing year: 2010-11-24
New York; NY; US
Printed / Made in
Language: English
93,49 € (DE)

BC; Hardcover, Softcover / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik; Wahrscheinlichkeitsrechnung und Statistik; Verstehen; Multivariate statistics; Normal distribution; Random variable; Resampling; classification; expectation–maximization algorithm; principal component analysis; Probability Theory; Statistical Theory and Methods; Stochastik; BB

1. Why Multivariate Statistics?.- 2. Joint Distribution of Several Random Variables.- 3. The Multivariate Normal Distribution.- 4. Parameter Estimation.- 5. Discrimination and Classification, Round 1.- 6. Statistical Inference for Means.- 7. Discrimination and Classification, Round 2.- 8. Linear Principal Component Analysis.- 9. Normal Mixtures.- Appendix: Selected Results From Matrix Algebra.- A.0. Preliminaries.- A.1. Partitioned Matrices.- A.2. Positive Definite Matrices.- A.3. The Cholesky Decomposition.- A.4. Vector and Matrix Differentiation.- A.5. Eigenvectors and Eigenvalues.- A.6. Spectral Decomposition of Symmetric Matrices.- A.7. The Square Root of a Positive Definite Symmetric Matrix.- A.8. Orthogonal Projections on Lines and Planes.- A.9. Simultaneous Decomposition of Two Symmetric Matrices.

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