Presents the main results of the modern theory of multivariate statistics to those who would appreciate a concise and mathematically rigorous treatment.
Theory of multivariate statistics
β Scribed by Martin Bilodeau, David Brenner
- Publisher
- Springer
- Year
- 1999
- Tongue
- English
- Leaves
- 305
- Series
- Springer texts in statistics
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
- Linear algebra --
- Random vectors --
- Gamma, Dirichlet, and F distributions --
- Invariance --
- Multivariate normal --
- Multivariate sampling --
- Wishart distributions --
- Tests on mean and variance --
- Multivariate regression --
- Principal components --
- Canonical correlations --
- Asymptotic expansions --
- Robustness --
- Bootstrap confidence regions and tests --
A. Inversion formulas --
B. Multivariate cumulants --
C. S-plus functions
π SIMILAR VOLUMES
The book aims to present a wide range of the newest results on multivariate statistical models, distribution theory and applications of multivariate statistical methods. A paper on Pearson-Kotz-Dirichlet distributions by Professor N Balakrishnan contains main results of the Samuel Kotz Memorial Lect
The book aims to present a wide range of the newest results on multivariate statistical models, distribution theory and applications of multivariate statistical methods. A paper on Pearson-Kotz-Dirichlet distributions by Professor N Balakrishnan contains main results of the Samuel Kotz Memorial Lect
<p><span>Rebecca M. Warnerβs bestselling </span><span>Applied Statistics: From Bivariate Through Multivariate Techniques</span><span> has been split into two volumes for ease of use over a two-course sequence. </span><span>Applied Statistics II: Multivariable and Multivariate Techniques, </span><spa