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 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: 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: This paper describes an analysis of data anomalies on computer records on 246 federally-insured mortgages. Twenty-three of the corresponding mortgages were sampled and all were found to have identical amortization plans and to have been insured under the same insurance fund. The question posed, in probabilistic terms, is the following: How many of the remaining 223 mortgages are identical in these two aspects to the 23 sampled mortgages?

Description: The purpose of this paper is to perform conjugate Bayesian analysis on the negative binomial distribution with the goal of providing a standard by which approximate credibility formulas and approximate predictive distriubtion may be judged. From Actuarial Research Clearing House 1993, VOL. 1.

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

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: 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.

Description: This work describes a study undertaken to determine whether the Federal Housing Administration's 'FHA' single-family-home mortgage insurance program for investor 'non-occupant' loans should be modified. The sample data were analyzed using both Bayesian and sample reuse procedures. A commentary on the paper is included.

Description: The problem of estimation of a tabular survival model from complete samples is considered from a Bayesian approach. If a life test involves a large cohort group, then data is typically given as a grouped data set. The survival function St is usually estimated by the moment estimator. We approximate the joint prior distribution of the unknown unconditional failure probabilities by a Dirichlet distribution, and then use a linear relationship between St and the conditional survival probabilities to obtain a Bayes estimator of St.