Description: The purpose of this paper is to introduce the use of least squares for estimating parameters of mortality curves and discuss the advantages of this method.

Description: From a session at the Spring regional meeting of the Society of Actuaries held in Atlanta, Georgia, May 24-25, 1999 Presenters offer a preview of an actual Course 7 dealing with applied modeling.

Description: This paper has two related purposes: first, to introduce a new class of Moving Weighted Average MWA graduation formulas where the coefficients are determined in accordance with the relative emphasis placed on smoothness and fit by the graduator, and second, to consider the question regarding what value of n to use when graduating by MWA formula. From the Actuarial Research Clearing House, 1978, Vol.1.

Description: This session is from the 1976 Washington D.C. Meeting and discusses qualitative and quantitative models for forecasting. The session is a general teaching session and not for experts.

Description: This chapter introduces a few probability distributions that play an important role in understanding and analyzing healthcare data. While theoretical in nature, these distributions model real life if appropriately chosen. Probability distributions are mathematical representations of how statistical data behave.

Description: An exploration of the seasonality of mortality and how total population mortality is related to flu and pneumonia mortality.

Description: From a session at the Spring regional meeting of the Society of Actuaries held in Atlanta, Georgia, May 24-25, 1999 Year 2000 and Beyond: Society of Actuaries New Course: Applied Modeling Demonstration Charts 1 & 2 from that presentation

Description: From a session at the Spring regional meeting of the Society of Actuaries held in Atlanta, GA May 24-25, 1999: Year 2000 and Beyond: Society of Actuaries New Course: Applied Modeling Demonstration: Charts 3 & 4 from that presentation

Description: This abstract describes a paper in which several issues surrounding the 2011 paper “Copula Regression”, Variance volume 5-issue1, by Rahul A. Parsa and Stuart A. Klugman, are discussed.

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.