Description: The purpose of this paper is to illustrate the method of Lagrange multipliers complete with simple examples. The author suggests that this methodology is ideally suited to the investigation of minimum variance plans. From the Actuarial Research Clearing House 1987 Vol. 1.

Description: This paper's objectives are to reduce the variation of life expectancy due to changes in the closing out method and give more homogeneous old age mortality surface for the Algerian population. The paper will also provide readers with a general methodology to extend mortality to old ages for the Algerian population starting from adult mortality data.

Description: The presentation of the simplex algorithm in 'A Study Manual For Operations Research' [edited by Eugene A. Narragon] is difficult to follow. The purpose of this note is to show that a better understanding can be obtained by means of a geometric interpretation and the exchange method.

Description: This presentation compares continuous-time multi-factor affine cohort mortality models and presents estimation results for an affine multi-factor, multi-cohort mortality model.

Description: This abstract describes a paper that introduces an approach to sensitivity analysis for quantitative risk models such as those used in solvency calculations.

Description: In this paper, the unconditional probability density functions of portfolio claim amounts based on several assumed risk distributions are found. From the Actuarial Research Clearing House 1994 Vol. 2 .

Description: This abstract describes a paper that proposes a multi-population Global Vector Autoregression (GVAR) mortality model, in which the joint mortality dynamics of all populations are formulated in a large vector autoregression model with a set of contemporaneous global mortality factors.

Description: This paper expands the calculation of a group's credibility factor from a traditional univariate one-dimensional single layer model to: 1. a univariate one dimensional two layer model, 2. a multivariate one dimensional single layer model, and 3. a univariate two dimensional single layer models.