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Gaussian proces models for mortality rates and improvement factors

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      <subfield code="a">Ludkovski, Mike</subfield>
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      <subfield code="a">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.</subfield>
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      <subfield code="a">Mortalidad</subfield>
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      <subfield code="a">Risk, Jimmy</subfield>
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      <subfield code="d">Belgium : ASTIN and AFIR Sections of the International Actuarial Association</subfield>
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      <subfield code="g">03/09/2018 Volumen 48 Número 3 - septiembre 2018 , p. 1307-1347</subfield>
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