Description: This paper shows how discrete multivariate analysis or multidimensional contingency table methods may be applied to data arising in actuarial work. A brief introduction to the theory is followed by two detailed examples of its application. Finally, the concluding remarks indicate how the procedure could be incorporated into a complete rate-making procedure. This work was performed for the U.S. Department of Housing and Urban Development.

Description: This paper presents an approach to analyzing continuing care retirement community [CCRC] data, and demonstrates the methods using data from a large CCRC. It is assumed that residents make transitions among a number of states that represent the levels of care required by residents. There is randomness associated with both the transition times and the states entered at these times. The model is conveniently characterized in terms of transition intensity functions, which represent the instantaneous rates of transition between pairs of states.

Description: The conventional way to analyze grouped observations on a single variable is to construct histograms or, sometimes, fit a normal distribution. We extend this latter approach by allowing for transformations to near normality.

Description: The study of Employee Benefits has always been aided by using financial algorithms. During recent semesters, the Lotus 1-2-3 package Lotus has been introduced to students due to the explosion of its use in the business community. This paper will show how our students use Lotus to design a spreadsheet for computing minimum annual distributions from tax-sheltered plans.

Description: This paper deals with how the credibility levels change based on this lack knowledge. Group insuraace models are used, bill some of tile techniques could apply to any insurance risk.