Forecasting mortality rates with functional signatures

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      <subfield code="a">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</subfield>
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