Univariate Geometric Stable Laws

Authors: Kozubowski T.J.¹; Rachev S.T.²

Source: Journal of Computational Analysis and Applications, Volume 01, Number 2, April 1999 , pp. 177-217(41)

Publisher: Springer

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Abstract:

The paper summarizes recent advances in the theory of geometric stable (GS) distributions. The results presented include parametrizations, characterizations, mixture representations, properties, asymptotic and convergent series expansions of densities and distribution functions, moments and tail behavior, simulation, and estimation.

Keywords: Geometric compound; heavy-tail modeling; Linnik distribution; Mittag–Leffler law; random summation

Language: English

Document Type: Research article

Affiliations: 1: Department of Mathematics, The University of Tennessee at Chattanooga, Chattanooga, Tennessee 37403 2: Department of Statistics and Applied Probability, University of California at Santa Barbara, Santa Barbara, California 93106

Publication date: 1999-04-01