The Multivariate Normal Distribution - Tapa dura

Libro 12 de 160: Springer Series in Statistics

Tong, Y. L.

 
9783540970620: The Multivariate Normal Distribution

Sinopsis

This text represents a comprehensive treatment of the results related to the multivariate normal distribution. In addition to the classical topics on distribution theory, correlation analysis and sampling distributions, it also contains recent results reported in relevant literature. The material is organized in a unified modern approach, and the main themes are dependence, probability inequalities, and their roles in theory and applications. Some of the properties (such as log-concavity, unimodality, Schurconcavity and total positivity) of a multivariate normal density function are discussed, and results that follow from these properties and reviewed. The volume also includes tables of the equi-coordinate percentage points and probability inequalities for exchangeable normal variables. The volume should be accessible to graduate students and advanced undergraduates in statistics, mathematics, and related applied areas, and can be used as a reference in a course on multivariate analysis.

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Reseña del editor

This text represents a comprehensive treatment of the results related to the multivariate normal distribution. In addition to the classical topics on distribution theory, correlation analysis and sampling distributions, it also contains recent results reported in relevant literature. The material is organized in a unified modern approach, and the main themes are dependence, probability inequalities, and their roles in theory and applications. Some of the properties (such as log-concavity, unimodality, Schurconcavity and total positivity) of a multivariate normal density function are discussed, and results that follow from these properties and reviewed. The volume also includes tables of the equi-coordinate percentage points and probability inequalities for exchangeable normal variables. The volume should be accessible to graduate students and advanced undergraduates in statistics, mathematics, and related applied areas, and can be used as a reference in a course on multivariate analysis.

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