Symmetric Multivariate and Related Distributions
Published on 18. January 2018
230 pages
978-1-351-08549-6 (ISBN)
Description
Since the publication of the by now classical Johnson and Kotz Continuous Multivariate Distributions (Wiley, 1972) there have been substantial developments in multivariate distribution theory especially in the area of non-normal symmetric multivariate distributions. The book by Fang, Kotz and Ng summarizes these developments in a manner which is accessible to a reader with only limited background (advanced real-analysis calculus, linear algebra and elementary matrix calculus). Many of the results in this field are due to Kai-Tai Fang and his associates and appeared in Chinese publications only.
A thorough literature search was conducted and the book represents the latest work - as of 1988 - in this rapidly developing field of multivariate distributions. The authors are experts in statistical distribution theory.
A thorough literature search was conducted and the book represents the latest work - as of 1988 - in this rapidly developing field of multivariate distributions. The authors are experts in statistical distribution theory.
More details
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
File size
7,66 MB
ISBN-13
978-1-351-08549-6 (9781351085496)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Kai-Tai Fang | Samuel Kotz | Kai W. Ng
Symmetric Multivariate and Related Distributions
Book
11/2017
1st Edition
Taylor & Francis
€235.22
Shipment within 15-20 days
Persons
Kai-Tai Fang - Institute of Applied Mathematics, Academia Sinica, P.O. Box 2734 100080 Beijing, China.
Samuel Kotz - Department of Management Science and Statistics University of Maryland College Park, Md. 20742, USA.
Kai W. Ng - Department of Statistics, University of Hong Kong, Hong Kong.
Samuel Kotz - Department of Management Science and Statistics University of Maryland College Park, Md. 20742, USA.
Kai W. Ng - Department of Statistics, University of Hong Kong, Hong Kong.
Content
Preface, 1: Preliminaries, 2: Spherically and elliptically symmetric distributions, 3: Some subclasses of elliptical distributions, 4: Characterizations, 5: Multivariate ?1-norm symmetric distributions, 6: Multivariate Liouville distributions, 7: ?-Symmetric distributions, References, Index
