A First Course in Multivariate Statistics: Springer Texts in Statistics
Autor Bernard Fluryen Limba Engleză Hardback – 15 aug 1997
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Springer – 15 aug 1997 | 709.42 lei 38-44 zile |
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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
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
GraduateCuprins
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