Forecasting mortality rates with functional signatures

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<title>Forecasting mortality rates with functional signatures</title>
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<namePart>Pathmanathan, Dharini</namePart>
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<namePart>Dabo-Niang, Sophie</namePart>
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<abstract displayLabel="Summary">This 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</abstract>
<note type="statement of responsibility">Zhong Jing Yap, Dharini Pathmanathan and Sophie Dabo-Niang</note>
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<topic>Modelos matemáticos</topic>
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<topic>Estadística matemática</topic>
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<topic>Cálculo integral</topic>
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<topic>Predicciones estadísticas</topic>
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<subject xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="MAPA20080555306">
<topic>Mortalidad</topic>
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<topic>Tablas de mortalidad</topic>
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<topic>Proyecciones demográficas</topic>
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<title>Astin bulletin</title>
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<publisher>Belgium : ASTIN and AFIR Sections of the International Actuarial Association</publisher>
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<identifier type="issn">0515-0361</identifier>
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<text>29/01/2025 Volume 55 Issue 1 - January 2025 , p. 97 - 120</text>
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