Multivariate statistics : high-dimensional and large-sample approximations /

A comprehensive examination of high-dimensional analysis of multivariate methods and their real-world applications Multivariate Statistics: High-Dimensional and Large-Sample Approximations is the first book of its kind to explore how classical multivariate methods can be revised and used in place of...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Fujikoshi, Yasunori, 1942-
Otros Autores: Ulyanov, Vladimir V., 1953-, Shimizu, Ryoichi, 1931-
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Hoboken, N.J. : Wiley, ©2010.
Colección:Wiley series in probability and statistics.
Temas:
Multivariate analysis.
Approximation theory.
Multivariate Analysis
Analyse multivariée.
Théorie de l'approximation.
MATHEMATICS > Probability & Statistics > Multivariate Analysis.
Approximation theory
Multivariate analysis
dissertations.
Academic theses
Academic theses.
Thèses et écrits académiques.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Front Matter
  • Multivariate Normal and Related Distributions
  • Wishart Distribution
  • Hotelling's T and Lambda Statistics
  • Correlation Coefficients
  • Asymptotic Expansions for Multivariate Basic Statistics
  • MANOVA Models
  • Multivariate Regression
  • Classical and High-Dimensional Tests for Covariance Matrices
  • Discriminant Analysis
  • Principal Component Analysis
  • Canonical Correlation Analysis
  • Growth Curve Analysis
  • Approximation to the Scale-Mixted Distributions
  • Approximation to Some Related Distributions
  • Error Bounds for Approximations of Multivariate Tests
  • Error Bounds for Approximations to Some Other Statistics
  • Appendix
  • Bibliography
  • Index
  • Wiley Series in Probability and Statistics.
  • Multivariate normal and related distributions
  • Wishart distribution
  • Hotelling's T² and lambda statistics
  • Correlation coefficents
  • Asymptotic expansions from multivariate basic statistics
  • MANOVA models
  • Multivariate regression
  • Classical and high-dimensional tests for covariance matrices
  • Discriminant analysis
  • Principal component analysis
  • Canonical correlation analysis
  • Growth curve analysis
  • Approximation to the scale-mixted distributions
  • Approximation to some related distributions
  • Error bounds for approximations of multivariate tests
  • Error bounds for approximations to some other statistics
  • Appendix.

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