Description: This paper presents a random selection method with the Monte Carlo simulation technique in the estimation of loss reserves. The future loss development factors are randomly selected from a weighted empirical distribution of observed loss development factors. This nonparametric approach provides an estimate of the distribution of total loss reserve.

Description: There are three commonly used methods for compiling exposure and death data for use in obtaining crude mortality rates. They are lives, policies and amounts of insurance. This paper investigates the properties of estimators based on lives, amounts and robust alternatives. It is concluded that lives provide the best estimator, even when there is a moderate dependence of mortality rates on amounts of insurance. Presented at the Fourteenth Actuarial Research Conference, lowa City, lowa, September 6, 1979.

Description: Users of statistical packages should be more aware of the influence that outlying data points can have on their statistical analyses. Robust procedures provide formal methods to spot these outliers and reduce their influence. While a few robust procedures are mentioned in this article, one is emphasized and it is motivated by maximum likelihood estimation to make it seem more natural. In this article, the author will try to provide some background, beginning with maximum likelihood estimation of one parameter, that will hopefully make robust estimation seem natural and rather easy.

Description: The theory underlying the Moving Weighted Average graduation method is restated in the language of linear algebra which provides for an enrichment of the family of formulas. A comparison of the results of applying six members of the family to 100 simulated data sets is provided.