ON THE EVALUATION OF MULTIVARIATE COMPOUND DISTRIBUTIONS WITH CONTINUOUS SEVERITY DISTRIBUTIONS AND SARMANOV'S COUNTING DISTRIBUTION

Details

Serval ID
serval:BIB_830EEDB3E432
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
ON THE EVALUATION OF MULTIVARIATE COMPOUND DISTRIBUTIONS WITH CONTINUOUS SEVERITY DISTRIBUTIONS AND SARMANOV'S COUNTING DISTRIBUTION
Journal
ASTIN Bulletin
Author(s)
Tamraz Maissa, Vernic Raluca
ISSN
0515-0361
1783-1350
Publication state
Published
Issued date
05/2018
Peer-reviewed
Oui
Volume
48
Number
02
Pages
841-870
Language
english
Abstract
In this paper, we present closed-type formulas for some multivariate compound distributions with multivariate Sarmanov counting distribution and independent Erlang distributed claim sizes. Further on, we also consider a type-II Pareto dependency between the claim sizes of a certain type. The resulting densities rely on the special hypergeometric function, which has the advantage of being implemented in the usual software. We numerically illustrate the applicability and efficiency of such formulas by evaluating a bivariate cumulative distribution function, which is also compared with the similar function obtained by the classical recursion-discretization approach.
Keywords
Multivariate compound model, sarmanov's multivariate discrete distribution, Erlang distribution, type-II Pareto multivariate distribution, hypergeometric function
Web of science
Create date
24/03/2018 20:49
Last modification date
20/08/2019 15:43
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