Description: In this paper two theorems concerning the optimality of the perfect-fit and perfect-smoothness graduations are proved. Two examples are presented and some difficulties with regard to computational feasibility are reviewed. A discussion of the paper follows. From Transactions of Society of Actuaries 1978, Vol. 30.

Description: This paper defines a general model for arbitrary units and gives formulas for computing the variance and mean squared error of decrement estimators. It is observed that, in small studies, the mean squared error is reduced by counting lives, even if the probability of death depends somewhat on the amount of insurance. From Transactions of Society of Actuaries 1981, Vol. 33.

Description: Because actuaries fit models for a variety of situations, particularly with regard to data modifications, it is useful to have a single approach. Though not optimal or exact for a particular model or data structure, the method should be reasonable for most all settings. Such a method is proposed in this article. Actuarial Research Clearing House 2003, VOL. 1

Description: In this paper the ad-hoc Bayesian derivation of the Whittaker method is replaced with a formal Bayesian specification, and then it is shown that with this specification it is possible to complete the graduation without making an arbitrary selection of the smoothing parameter. From Actuarial Research Clearing House 1992, 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.