Kai-Tai Fang, Samuel Kotz, Kai W. Ng

Symmetric Multivariate and Related Distributions (eBook, ePUB)

• Format: ePub

Produktbeschreibung

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.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 230
• Erscheinungstermin: 18. Januar 2018
• Englisch
• ISBN-13: 9781351093941
• Artikelnr.: 50921160

Autorenporträt

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.