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Gaussian proces models for mortality rates and improvement factors

Recurso electrónico / Electronic resource
MAP20180032059
Ludkovski, Mike
Gaussian proces models for mortality rates and improvement factors / Mike Ludkovski, Jimmy Risk, Howard Zail
Sumario: We develop a Gaussian process (GP) framework for modeling mortality rates and mortality improvement factors. GP regression is a nonparametric, data driven approach for determining the spatial dependence in mortality rates and jointly smoothing raw rates across dimensions, such as calendar year and age. The GP model quantifies uncertainty associated with smoothed historical experience and generates full stochastic trajectories for out-of-sample forecasts
En: Astin bulletin. - Belgium : ASTIN and AFIR Sections of the International Actuarial Association = ISSN 0515-0361. - 03/09/2018 Volumen 48 Número 3 - septiembre 2018 , p. 1307-1347
1. Cálculo actuarial . 2. Modelos actuariales . 3. Modelos predictivos . 4. Mortalidad . 5. Data driven . I. Risk, Jimmy . II. Zail, Howard . III. Título.