A New Toolkit for Mortality Data Analytics

Krömer S, Stummer W (2019)

Publication Type: Book chapter / Article in edited volumes

Publication year: 2019

Publisher: Springer

Edited Volumes: Stochastic Models, Statistics and Their Applications

Series: Springer Proceedings in Mathematics & Statistics

Book Volume: 294

Pages Range: 393-407

Conference Proceedings Title: Springer Proceedings in Mathematics and Statistics

Event location: Dresden DE

ISBN: 9783030286644

DOI: 10.1007/978-3-030-28665-1_30

Abstract

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.

Authors with CRIS profile

Sarah Krömer Lehrstuhl für Versicherungswirtschaft und Risikomanagement Wolfgang Stummer Professur für Mathematik

How to cite

APA:

Krömer, S., & Stummer, W. (2019). A New Toolkit for Mortality Data Analytics. In Ansgar Steland, Ewaryst Rafajlowicz, Ostap Okhrin (Eds.), Stochastic Models, Statistics and Their Applications. (pp. 393-407). Springer.

MLA:

Krömer, Sarah, and Wolfgang Stummer. "A New Toolkit for Mortality Data Analytics." Stochastic Models, Statistics and Their Applications. Ed. Ansgar Steland, Ewaryst Rafajlowicz, Ostap Okhrin, Springer, 2019. 393-407.

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