Mortality Rate Modeling of Joint Lives and Survivor Insurance Contracts Tested by A Novel Unilateral Dependence Measure

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Recently, nonsymmetric measures of dependence have started to attract attention, and several continuous entropy-like nonsymmetric dependence measures have been proposed. Based on Onicescu's information energy, we have introduced in previous work a nonsymmetric dependence measure between two discrete random variables. In the present paper, we analyze the continuous version of this measure. We deduct that there are important differences when switching from the discrete to the continuous measure. Then we apply this continuous unilateral dependence measure to a real-world challenge: mortality rate modeling for life insurance industry. We consider joint male-female pairs (married, but not necessarily from the same family) belonging to the same policy group, and analyze the unilateral interactions between the male-female mortality data samples for the purpose of stochastic model testing and validation of risk variables in the insurance world.


This article was originally published in 2016 IEEE Symposium Series on Computational Intelligence (SSCI). The full-text article from the publisher can be found here.

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2016 IEEE Symposium Series on Computational Intelligence (SSCI)


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