scholarly journals When is a Riesz distribution a complex measure?

2011 ◽  
Vol 139 (4) ◽  
pp. 519-534 ◽  
Author(s):  
Alan D. Sokal
Keyword(s):  
Complex Measure ◽  
Riesz Distribution

scholarly journals Tooth loss is a complex measure of oral disease: Determinants and methodological considerations

2018 ◽  
Vol 46 (6) ◽  
pp. 555-562 ◽  
Author(s):  
Simon Haworth ◽  
Dmitry Shungin ◽  
So Young Kwak ◽  
Hae-Young Kim ◽  
Nicola X. West ◽  
...  
Keyword(s):  
Tooth Loss ◽  
Oral Disease ◽  
Complex Measure ◽  
Methodological Considerations

scholarly journals EXTENSION OF THE OLKIN AND RUBIN CHARACTERIZATION TO THE WISHART DISTRIBUTION ON HOMOGENEOUS CONES

2011 ◽  
Vol 14 (04) ◽  
pp. 591-611 ◽  
Author(s):  
I. BOUTOURIA ◽  
A. HASSAIRI ◽  
H. MASSAM
Keyword(s):  
Wishart Distribution ◽  
Symmetric Cone ◽  
Symmetric Matrices ◽  
Riesz Distribution ◽  
Homogeneous Cones ◽  
Homogeneous Cone

The Wishart distribution on a homogeneous cone is a generalization of the Riesz distribution on a symmetric cone which corresponds to a given graph. The paper extends to this distribution, the famous Olkin and Rubin characterization of the ordinary Wishart distribution on symmetric matrices.

scholarly journals The multiparameter t’distribution

Filomat ◽  
2019 ◽  
Vol 33 (13) ◽  
pp. 4137-4150 ◽  
Author(s):  
Emna Ghorbel ◽  
Mahdi Louati
Keyword(s):  
Mean Squared Error ◽  
Natural Extension ◽  
Expectation Maximization Algorithm ◽  
Infinite Divisibility ◽  
Cholesky Decomposition ◽  
Wishart Distribution ◽  
Normal Vector ◽  
Riesz Distribution ◽  
Estimated Parameters ◽  
T Distribution

This research paper stands for an extension to the multivariate t?distribution introduced in 1954 by Cornish, Dunnett and Sobel, namely the multiparameter t?distribution. This distribution is expressed in two different ways. The first way invests the mixture of a normal vector with a natural extension to the Wishart distribution, that is the Riesz distribution on symmetric matrices. The second one rests upon the Cholesky decomposition of the Riesz matrix. An algorithm for generating this distribution is investigated using the Riesz distribution arising obtained through not only the distribution of the empirical normal covariance matrix for samples with monotone missing data but also through Cholesky decomposition. In addition, Some fundamentals properties of the multiparameter t?distribution such as the infinite divisibility are identified. Besides, the Expectation Maximization algorithm is used to estimate its parameters. Finally, the performance of these estimators is assessed by means of the Mean Squared Error between the true and the estimated parameters.

scholarly journals On Itô's complex measure condition

2003 ◽  
pp. 65-80 ◽  
Author(s):  
Larry Chen ◽  
Scott Dobson ◽  
Ronald Guenther ◽  
Chris Orum ◽  
Mina Ossiander ◽  
...  
Keyword(s):  
Complex Measure
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