A New Toolkit for Mortality Data Analytics - Krömer, Sarah; Stummer, Wolfgang (Stochastic Models, Statistics and Their Applications, 2019)
For the calculation of premiums, financial reserves, annuities, pension benefits, various benefits of social insurance programs, and many other quantities, a realistic representation of mortality rates is of fundamental essence. We achieve this by a new far-reaching and flexible approach for the smoothing and error-correcting of crude rates, based on the recently developed scaled Bregman distances of Stummer (Proc Appl Math Mech 7(1):1050503–1050504, 2007, [22]), Stummer and Vajda (IEEE Trans Inform Theory 58(3):1277–1288, 2012, [25]), Kißlinger and Stummer (Recent Advances in Robust Statistics – Theory and Applications, pp. 81–113. Springer, India, 2016, [12]), which are generalizations of the well-known Kullback–Leibler information divergence (relative entropy). As illuminations, we present several examples and a concrete data analysis.
CRIS-Team Scopus Importer:2019-12-10
Keywords: Mortality rates; Scaled Bregman distances; Smoothing/Graduation