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A Characterization of the Compound Multiparameter Hermite Gamma Distribution via Gauss’s Principle
Author
Source
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-10-31
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
We consider the class of those distributions that satisfy Gauss's principle (the maximum likelihood estimator of the mean is the sample mean) and have a parameter orthogonal to the mean.
It is shown that this so-called “mean orthogonal class” is closed under convolution.
A previous characterization of the compound gamma characterization of random sums is revisited and clarified.
A new characterization of the compound distribution with multiparameter Hermite count distribution and gamma severity distribution is obtained.
American Psychological Association (APA)
Hürlimann, Werner. 2013. A Characterization of the Compound Multiparameter Hermite Gamma Distribution via Gauss’s Principle. The Scientific World Journal،Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-1032955
Modern Language Association (MLA)
Hürlimann, Werner. A Characterization of the Compound Multiparameter Hermite Gamma Distribution via Gauss’s Principle. The Scientific World Journal No. 2013 (2013), pp.1-7.
https://search.emarefa.net/detail/BIM-1032955
American Medical Association (AMA)
Hürlimann, Werner. A Characterization of the Compound Multiparameter Hermite Gamma Distribution via Gauss’s Principle. The Scientific World Journal. 2013. Vol. 2013, no. 2013, pp.1-7.
https://search.emarefa.net/detail/BIM-1032955
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1032955