The paper introduces a penalized distributed lag non-linear Lee-Carter framework that adds temperature and influenza effects, negative binomial overdispersion, SARIMA dynamics, and copula dependence for improved regional weekly mortality forecasts on French data 1990-2019.
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CNN-LSTM and GNN-LSTM models added to a Lee-Carter baseline reduce test MSE by about 24% versus MortFCNet on French regional mortality data from 1990-2019, with largest gains at oldest ages.
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Climate-Driven Mortality Forecasting Using Deep Learning
CNN-LSTM and GNN-LSTM models added to a Lee-Carter baseline reduce test MSE by about 24% versus MortFCNet on French regional mortality data from 1990-2019, with largest gains at oldest ages.