𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Sequential credibility evaluation for symmetric location claim distributions

✍ Scribed by Zinoviy Landsman; Udi E. Makov


Publisher
Elsevier Science
Year
1999
Tongue
English
Weight
89 KB
Volume
24
Category
Article
ISSN
0167-6687

No coin nor oath required. For personal study only.

✦ Synopsis


The traditional linear credibility formula provides an exact expression for the predictive mean when the conditional loss distributions belong to the exponential dispersion family (EDF) and when the prior distribution is conjugate. When the claim size follows a distribution outside this family, the credibility formula offers an inaccurate estimation of the mean future claim. The established analogy between the credibility formula and stochastic approximation [Landsman, Z., Makov, U., 1999. On Stochastic Approximation and Credibility. Scand. Actuarial J., to appear] offers a way of devising credibility estimation for distributions other than members of the EDF. In this paper we suggest sequential credibility estimators which are suited to deal with distributions belonging to the symmetric location dispersion family.


πŸ“œ SIMILAR VOLUMES


On the efficient evaluation of ruin prob
✍ HansjΓΆrg Albrecher; Florin Avram; Dominik Kortschak πŸ“‚ Article πŸ“… 2010 πŸ› Elsevier Science 🌐 English βš– 765 KB

In this paper we propose a highly accurate approximation procedure for ruin probabilities in the classical collective risk model, which is based on a quadrature/rational approximation procedure proposed in [2]. For a certain class of claim size distributions (which contains the completely monotone d

A credibility-based fuzzy location model
✍ H.C.W. Lau; Zhong-Zhong Jiang; W.H. Ip; Dingwei Wang πŸ“‚ Article πŸ“… 2010 πŸ› Elsevier Science 🌐 English βš– 1020 KB

## a b s t r a c t Facility location problem is one of the most critical elements in the design of distribution systems, and numerous studies have focused on this issue. However, facility location theory and guidelines for B2C firms are sparse. In this paper, with regard to the customer characteris