Description: This paper outlines a statistical modeling framework for fitting mortality laws to mortality experience data. The process can be used as an alternative to traditional graduation techniques used in mortality table development.

Description: In this paper, we study a survival regression model known as Cox's proportional Hazards model. We assume that the data available are already grouped and develop a minimum distance estimation procedure that is also applicable when the data are also left or right censored. Asymptotic properties of the estimators are established and the numerical implementation of the method based on an iterated reweighted least squares algorithm is discussed.

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: Second article in a series on how to use predictive analytics to improve the development of long-term care projection assumptions.