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On univariate and bivariate generalized gamma convolutions
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
2009 (English)In: Journal of Statistical Planning and Inference, ISSN 0378-3758, E-ISSN 1873-1171, Vol. 139, no 11, 3759-3765 p.Article in journal (Refereed) Published
Abstract [en]

This paper has two parts. In the first part some results for generalized gamma convolutions (GGCs) are reviewed. A GGC is a limit distribution for sums of independent gamma variables. In the second part, bivariate gamma distributions and bivariate GGCs are considered. New bivariate gamma distributions are derived from shot-noise models. The remarkable property hyperbolic complete monotonicity (HCM) for a function is considered both in the univariate case and in the bivariate case.

Place, publisher, year, edition, pages
Amsterdam: Elsevier, 2009. Vol. 139, no 11, 3759-3765 p.
Keyword [en]
Bivariate gamma distribution, Generalized gamma convolution, Hyperbolic complete monotonicity (HCM), Shot-noise models
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:umu:diva-19578DOI: 10.1016/j.jspi.2009.05.015OAI: oai:DiVA.org:umu-19578DiVA: diva2:202049
Conference
The VIII Tartu Conference on Multivariate Statistics organized jointly with the VI Conference on Multivariate Distributions with Fixed Marginals, Tartu, 26–29 June 2007
Note

Special Issue: The 8th Tartu Conference on Multivariate Statistics & The 6th Conference on Multivariate Distributions with Fixed Marginals

Available from: 2009-03-06 Created: 2009-03-06 Last updated: 2017-12-13Bibliographically approved

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CiteExportLink to record
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  • apa
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  • de-DE
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  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
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  • text
  • asciidoc
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