This up-to-date, comprehensive sourcebook treats data-oriented techniques as well as classical methods. Emphasis is on principles rather than mathematical detail, and coverage ranges from the practical problems of graphically representing high dimensional data to the theoretical problems relating to matrices of random variables. Each chapter serves as a self-contained survey of a specific topic. Includes many numerical examples, and over 1,100 references.
Rezensionen / Stimmen
"...an excellent introduction to statistical inference in the Multivariate Linear Model...it is a real achievement to discuss so many different topics in a single book of medium size." (ISCB News, December 2006) "The book...by George A. F. Server is [an] example of how a book should be written." (Journal of Statistical Computation and Simulation, March 2006)
Produkt-Info
Reihe
Auflage
Sprache
Verlagsort
Zielgruppe
Produkt-Hinweis
Broschur/Paperback
Klebebindung
Maße
Höhe: 229 mm
Breite: 152 mm
Dicke: 42 mm
Gewicht
ISBN-13
978-0-471-69121-1 (9780471691211)
Schweitzer Klassifikation
GEORGE A. F. SEBER is a Professor in the Department of Statistics at The University of Auckland in New Zealand.
Autor*in
Univ. of Auckland, New Zealand
Notation.
1. Preliminaries.
2. Multivariate Distributions.
3. Inference for the Multivariate Normal.
4. Graphical and Data-Oriented Techniques.
5. Dimension Reduction and Ordination.
6. Discriminant Analysis.
7. Cluster Analysis.
8. Multivariate Linear Models.
9. Multivariate Analysis of Variance and Covariance.
10. Special Topics.
Appendix A: Some Matrix Algebra.
Appendix B: Orthogonal Projections.
Appendix C: Order Statistics and Probability Plotting.
Appendix D: Statistical Tables.
Outline Solutions to Exercises.
References.
Index.
