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A First Course in Multivariate Statistics: Springer Texts in Statistics

Autor Bernard Flury
en Limba Engleză Hardback – 15 aug 1997
My goal in writing this book has been to provide teachers and students of multi­ variate statistics with a unified treatment ofboth theoretical and practical aspects of this fascinating area. The text is designed for a broad readership, including advanced undergraduate students and graduate students in statistics, graduate students in bi­ ology, anthropology, life sciences, and other areas, and postgraduate students. The style of this book reflects my beliefthat the common distinction between multivariate statistical theory and multivariate methods is artificial and should be abandoned. I hope that readers who are mostly interested in practical applications will find the theory accessible and interesting. Similarly I hope to show to more mathematically interested students that multivariate statistical modelling is much more than applying formulas to data sets. The text covers mostly parametric models, but gives brief introductions to computer-intensive methods such as the bootstrap and randomization tests as well. The selection of material reflects my own preferences and views. My principle in writing this text has been to restrict the presentation to relatively few topics, but cover these in detail. This should allow the student to study an area deeply enough to feel comfortable with it, and to start reading more advanced books or articles on the same topic.
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Specificații

ISBN-13: 9780387982069
ISBN-10: 038798206X
Pagini: 715
Ilustrații: XV, 715 p. 20 illus.
Dimensiuni: 193 x 242 x 46 mm
Greutate: 1.82 kg
Ediția:1997
Editura: Springer
Colecția Springer
Seria Springer Texts in Statistics

Locul publicării:New York, NY, United States

Public țintă

Graduate

Cuprins

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.

Recenzii

 
From a review:
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
"... is actually a very unique book that differs considerably from other multivariate texts. Flury should be applauded for his intention and effort to produce a new type of multivariate book that is neither a comprehensive theoretical treatise nor an encyclopedic methods cookbook. ... it is a welcome addition to the multivariate statistics literature. This is a well-written book with vivid and lively discussions."

Caracteristici

Begins at the elementary level, presenting the first principles of multivariate distributions * Includes cutting-edge topics such as the EM algorithm and principal component analysis * Examples from biology, anthropology, chemistry, and other areas are worked out in detail * The book contains a wealth of exercises, ranging from easy to advanced * Extremely thorough coverage of the topic Includes supplementary material: sn.pub/extras