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ArticleMachine learning techniques for mortality modeling

Philippe Deprez2017

Article2017

Machine learning techniques for mortality modeling

Philippe Deprez · Pavel V. Shevchenko · Mario V. Wüthrich

72 citations·0/0 files stored·European Actuarial Journal

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Insurance, Mortality, Demography, Risk Management Statistical Distribution Estimation and Applications Statistical Methods in Epidemiology

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References

1992Modeling and Forecasting U. S. Mortality 2006A cohort-based extension to the Lee–Carter model for mortality reduction factors 2009A Quantitative Comparison of Stochastic Mortality Models Using Data From England and Wales and the United States 2003Lee–Carter Mortality Forecasting: A Parallel Generalized Linear Modelling Approach for England and Wales Mortality Projections 2015StMoMo : An R Package for Stochastic Mortality Modeling 1983Volcano weather: the story of 1816, the year without a summer [Indonesia]

Cited by

2017Data Analytics for Non-Life Insurance Pricing 2019Application of Machine Learning to Mortality Modeling and Forecasting 2018AI in Actuarial Science 2022A Neural Approach to Improve the Lee-Carter Mortality Density Forecasts 2022Efficient use of data for LSTM mortality forecasting 2021Mind the Gap - Safely Incorporating Deep Learning Models into the Actuarial Toolkit 2022TREE-BASED MACHINE LEARNING METHODS FOR MODELING AND FORECASTING MORTALITY

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Details

Year2017

Typearticle

Published2017-06-06

VenueEuropean Actuarial Journal

ISSN-L2190-9733

Languageen

Citations72

Files0 public / 0

ShelfInsurance, Mortality, Demography, Risk Management

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doi10.1007/s13385-017-0152-4

openalex_workW2593566717

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2019

A random forest algorithm to improve the Lee–Carter mortality forecasting: impact on q-forward