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Discrete -convex extremal distributions: Theory and applications
Authors:Cindy Courtois, Michel Denuit,S  bastien Van Bellegem
Affiliation:aInstitut des Sciences Actuarielles, Université catholique de Louvain, Belgium;bInstitut de Statistique, Université catholique de Louvain, Belgium
Abstract:Given a nondegenerate moment space with s fixed moments, explicit formulas for the discrete s-convex extremal distribution have been derived for s=1,2,3 (see [M. Denuit, Cl. Lefèvre, Some new classes of stochastic order relations among arithmetic random variables, with applications in actuarial sciences, Insurance Math. Econom. 20 (1997) 197–214]). If s=4, only the maximal distribution is known (see [M. Denuit, Cl. Lefèvre, M. Mesfioui, On s-convex stochastic extrema for arithmetic risks, Insurance Math. Econom. 25 (1999) 143–155]). This work goes beyond this limitation and proposes a method for deriving explicit expressions for general nonnegative integer s. In particular, we derive explicitly the discrete 4-convex minimal distribution. For illustration, we show how this theory allows one to bound the probability of extinction in a Galton–Watson branching process. The results are also applied to derive bounds for the probability of ruin in the compound binomial and Poisson insurance risk models.
Keywords:  mml44"  >  text-decoration:none   color:black"   href="  /science?_ob=MathURL&_method=retrieve&_udi=B6TY9-4JJGB50-5&_mathId=mml44&_user=10&_cdi=5613&_rdoc=14&_acct=C000069468&_version=1&_userid=6189383&md5=f15388419777366be34d6be82a7b36a4"   title="  Click to view the MathML source"   alt="  Click to view the MathML source"  >s-convex orders   Moment spaces   Stochastic extrema   Lundberg’  s bound   Branching process   Insurance risk model
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