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Forecasting mortality rates with functional signatures

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Tag12Valor
LDR  00000cab a2200000 4500
001  MAP20260001593
003  MAP
005  20260130102707.0
008  260129e20250129bel|||p |0|||b|eng d
040  ‎$a‎MAP‎$b‎spa‎$d‎MAP
084  ‎$a‎6
100  ‎$0‎MAPA20260001098‎$a‎Jing Yap, Zhong
24510‎$a‎Forecasting mortality rates with functional signatures‎$c‎Zhong Jing Yap, Dharini Pathmanathan and Sophie Dabo-Niang
520  ‎$a‎This study introduces an innovative methodology for mortality forecasting, which integrates signature-based methods within the functional data framework of the HyndmanUllah (HU) model. This new approach, termed the HyndmanUllah with truncated signatures (HUts) model, aims to enhance the accuracy and robustness of mortality predictions. By utilizing signature regression, the HUts model is able to capture complex, nonlinear dependencies in mortality data which enhances forecasting accuracy across various demographic conditions
650 4‎$0‎MAPA20080592042‎$a‎Modelos matemáticos
650 4‎$0‎MAPA20090033023‎$a‎Estadística matemática
650 4‎$0‎MAPA20080574871‎$a‎Cálculo integral
650 4‎$0‎MAPA20120011137‎$a‎Predicciones estadísticas
650 4‎$0‎MAPA20080555306‎$a‎Mortalidad
650 4‎$0‎MAPA20080599300‎$a‎Tablas de mortalidad
650 4‎$0‎MAPA20080618070‎$a‎Proyecciones demográficas
7001 ‎$0‎MAPA20260001104‎$a‎Pathmanathan, Dharini
7001 ‎$0‎MAPA20260001111‎$a‎Dabo-Niang, Sophie
7102 ‎$0‎MAPA20100017661‎$a‎International Actuarial Association
7730 ‎$w‎MAP20077000420‎$g‎29/01/2025 Volume 55 Issue 1 - January 2025 , p. 97 - 120‎$x‎0515-0361‎$t‎Astin bulletin‎$d‎Belgium : ASTIN and AFIR Sections of the International Actuarial Association