Time-series forecasting of mortality rates using deep learning
| Year of publication: |
2021
|
|---|---|
| Authors: | Perla, Francesca ; Richman, Ronald ; Scognamiglio, Salvatore ; Wüthrich, Mario V. |
| Published in: |
Scandinavian actuarial journal. - Stockholm : Taylor & Francis, ISSN 1651-2030, ZDB-ID 2029609-5. - Vol. 2021.2021, 7, p. 572-598
|
| Subject: | convolutional neural networks | human mortality database | Lee-Carter model | Mortality forecasting | recurrent neural networks | representation learning | time-series forecasting | Neuronale Netze | Neural networks | Sterblichkeit | Mortality | Prognoseverfahren | Forecasting model | Zeitreihenanalyse | Time series analysis | Theorie | Theory | Lernprozess | Learning process |
-
Accurate and explainable mortality forecasting with the LocalGLMnet
Perla, Francesca, (2024)
-
Quantile mortality modelling of multiple populations via neural networks
Corsaro, Stefania, (2024)
-
Point and interval forecasts of death rates using neural networks
Schnürch, Simon, (2022)
- More ...
-
Accurate and explainable mortality forecasting with the LocalGLMnet
Perla, Francesca, (2024)
-
A neural network extension of the Lee-Carter model to multiple populations
Richman, Ronald, (2021)
-
Discrimination-free insurance pricing
Lindholm, Mathias, (2022)
- More ...