Description: This abstract describes a paper in which two different simulation studies are made for dynamic financial analysis.

Description: This presentation shows how the the linear model is derived assuming that the force increases linearly over the year.

Description: View information about the 2019.1 Actuarial Research Conference Proceedings.

Description: This is article identifies and quantifies how one of several prospective cures for chronic conditions will impact healthcare.

Description: This poster describes the optimal investment and benefit payment problem for a target benefit pension with default risk and model uncertainty.

Description: We apply a class of linear classifier models under a flexible loss function to study binary classification problems. The loss function consists of two penalty terms, one penalizing false positive (FP) and the other penalizing false negative (FN), and can accommodate various classification targets by choosing a weighting function to adjust the impact of FP and FN on classification. We show, through both a simulated study and an empirical analysis, that the linear classifier models under certain parametric weight functions can outperform the logistic regression model and can be trained to meet flexible targeted rates on FP or FN.

Description: Review a report addressing the increasing prevalence and financial costs of diabetes in the United States.