Description: Abstract from a paper that describes results from a hierarchical Bayesian statistical model which predicts the probability of Non-Acceptable Claim, an unnecessary hospital stay, using hospital discharge claim records as inputs.

Description: The objective of this paper is to present a technical exposition of the rudiments of Bayesian statistics.

Description: In this paper the author presents an application of Bayesian forecasting methods to the estimation of reserves for outstanding claims. He assumes that the time number of periods it takes for the claims to be completely paid is fixed and known, that payments are made annually and that the development of partial payments follows a stable pay-off pattern. From Actuarial Research Clearing House, 2003, Vol 1.

Description: This paper presents an additional view of estimating parameters of the force of mortality using Bayesian methods. Some examples are provided. From Actuarial Research Clearing House 1993 VOL. 1.

Description: This paper shows how a graduation method may be developed as straight forward statistical estimation within a statistical theory based upon personal probability, that is, so-called Bayesian statistics. The method discussed is applicable to a broad range of graduation situations, but does assume the more specific property of the graduator's prior opinion with respect to mortality rates.

Description: A presentation of a mathematics/statistics based approach for determining credibility factors for possible use in group health insurance premium rate setting and experience refund setting. Includes supporting mathematical proofs of approach. Followed by discussions submitted by several people

Description: This paper examines the compatibility of the two models, in the hope that this exploration will prompt a greater cross-fertilization of ideas between the life actuarial branch which favors Bayesian models and the casualty branch which favors Hans Buhlmann models.

Description: This paper presents Bayesian models for analysis of claim lag data. The analysis of claim runoff patterns investigate the extraction of information on trend and seasonal patterns in incurred claims. This is investigated on the basis of individual group data, and also relative to a larger aggregation of pooled experience. The models are implemented based on Markov chain Monte Carlo methods. The models are applied to examples using simulated claim lag data. From Actuarial Research Clearing House, 2003, Vol. 1.