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: 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 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: Premium computation in a Bayesian context requires the use of a prior distribution [structure function] that the risk parameter follows in the heterogeneous portfolio. This paper contributes to the analysis of credibility theory by identifying the unique relationship between the prior distribution and credibility formula. The latter corresponds to a suggestive form of expressing the premium to be charged to a policyholder as a weighted sum of the sample mean and collective premium. Results for net premium principle and Poisson and negative binomial likelihood functions are shown.

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 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: This paper discusses the Bayesian graduation method of Kimeldorf and Jones and develops methods for managing four technical problems in their method. It also includes a discussion of the paper. From Transactions of Society of Actuaries 1977, Vol. 29.

Description: In this paper, the Bayesian model of collective risk theory is extended in the sense that a large class of distributions is used instead of a single one. The authors then investigate the sensitivity of variance premium principle when the structure function belongs to that class. According to robust Bayesian methodology, the uncertainty in the prior can be modeled by specifying a class of priors instead of a single one. The authors examine the ranges of the Bayesian premium, also called experience rated premium, when the priors belong to that class. Most of the robust Bayesian procedures developed measures of sensitivity of quantities which can be expressed in terms of posterior expectation [e.g., mean, variance and probability of given sets]. Nevertheless, relatively few papers have been related to measure Bayesian sensitivity of quantities which can be expressed in terms of ratio of two posterior expectations, as occurs in the variance premium principle. Appropriate techniques to solve this situation are considered. Unimodality turns out to be very convenient for modelling subjective beliefs about the risk parameter. The very common Poisson-Gamma model is developed in depth using this paper's methodology.

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.