Gaussian proces models for mortality rates and improvement factors

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<dc:creator>Ludkovski, Mike</dc:creator>
<dc:creator>Risk, Jimmy</dc:creator>
<dc:creator>Zail, Howard</dc:creator>
<dc:date>2018-09-03</dc:date>
<dc:description xml:lang="es">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.</dc:description>
<dc:identifier>https://documentacion.fundacionmapfre.org/documentacion/publico/es/bib/166191.do</dc:identifier>
<dc:language>eng</dc:language>
<dc:rights xml:lang="es">InC - http://rightsstatements.org/vocab/InC/1.0/</dc:rights>
<dc:subject xml:lang="es">Cálculo actuarial</dc:subject>
<dc:subject xml:lang="es">Modelos actuariales</dc:subject>
<dc:subject xml:lang="es">Modelos predictivos</dc:subject>
<dc:subject xml:lang="es">Mortalidad</dc:subject>
<dc:subject xml:lang="es">Data driven</dc:subject>
<dc:type xml:lang="es">Artículos y capítulos</dc:type>
<dc:title xml:lang="es">Gaussian proces models for mortality rates and improvement factors</dc:title>
<dc:relation xml:lang="es">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</dc:relation>
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