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A Class of Multivariate Skew Distributions

 

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  • Product Description
 

Flexible parametric distribution models that can represent both skewed and symmetric distributions, namely skew symmetric distributions, can be constructed by skewing symmetric kernel densities by using weighting distributions. In this book, we study a multivariate skew family that have either centrally symmetric or spherically symmetric kernel. Specifically, we define multivariate skew symmetric forms of uniform, normal, Laplace, and logistic distributions by using the cumulative distribution functions of the same distributions as weighting distributions. Matrix and array variate extensions of these distributions are also introduced herein. We propose an estimation procedure based on the maximum product of spacings method and model identification. This idea also leads to bounded model selection criteria that can be considered as alternatives to Akaike's and other likelihood based criteria when the unbounded likelihood may be a problem. Applications of skew symmetric distributions to data are also considered.

Product Specifications
SKU :COC67795
AuthorDeniz Akdemir
LanguageEnglish
BindingPaperback
Number of Pages136
Publishing Year2013-05-25T00:00:00.000
ISBN9783639512915
Edition1 st
Book TypeMathematics
Country of ManufactureIndia
Product BrandScholars' Press
Product Packaging InfoBox
In The Box1 Piece
Product First Available On ClickOnCare.com2015-07-08 00:00:00
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