Symmetric Multivariate and Related Distributions
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A01=Kai W. Ng
A01=Kai Wang Fang
A01=Kai-Tai Fang
A01=Samuel Kotz
advanced probability
Age Group_Uncategorized
Age Group_Uncategorized
Author_Kai W. Ng
Author_Kai Wang Fang
Author_Kai-Tai Fang
Author_Samuel Kotz
automatic-update
Bessel Distribution
Category1=Non-Fiction
Category=PBT
Cauchy Functional Equation
Complete Monotonicity
conditional
Continuous Complex Function
COP=United Kingdom
Cumulative Distribution Function
Delivery_Pre-order
Dirichlet Distribution
elliptical
elliptical distributions
eq_isMigrated=2
eq_nobargain
function
Infinite Dimensional Banach Space
Kai Wang Ng
Kai-Tai Fang
Kotz Type Distributions
Language_English
matrix calculus methods
Maximal Invariant
measurable
Multinormal Distribution
multivariate analysis
Multivariate Cauchy Distribution
Multivariate Distributions
Multivariate Laplace Distribution
non-normal distribution research
nonnegative
Nonnegative Measurable Function
Nonnegative Random Variable
PA=Temporarily unavailable
Positive Definite Square Root
Price_€100 and above
PS=Active
random
Random Orthogonal Matrix
Regular Conditional Distribution
Samuel Kotz
softlaunch
spherical
Spherical Distribution
spherically symmetric models
Standard Cauchy
Standard Cauchy Distribution
statistical theory
Stochastic Decomposition
Symmetric Kotz Type Distributions
Symmetric Stable Distribution
unit
variable
vector
Product details
- ISBN 9781315897943
- Weight: 590g
- Dimensions: 156 x 234mm
- Publication Date: 29 Nov 2017
- Publisher: Taylor & Francis Ltd
- Publication City/Country: GB
- Product Form: Hardback
- Language: English
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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.
