Standard tools to compare and evaluate mortality forecasting methods
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Updated
Sep 23, 2020 - R
Standard tools to compare and evaluate mortality forecasting methods
CoMoMo combines multiple mortality forecasts using different model combinations. See more from the paper here https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3823511
Forecast mortality using Compositional Data Lee-Carter model - R Package
Project for the Bayesian Statistics exam at University of Trieste
Improved Mortality Forecasts using Artificial Intelligence.
Lee Carter model and different cross-validation methods for mortality forecasting models, implemented in Python.
Mortality rate predictions for Italy in 2020 using Lee-Carter model and Recurrent Neural Networks
Modelling and forecasting cohort mortality
Modelling and forecasting adult age-at-death distributions
R package - Computing mortality rates from tobacco and alcohol related causes. This is a mirror of the code in the private Gitlab repository
The Double-Gap Life Expectancy Forecasting Model - R Package
Python implementations of different mortality modeling techniques (for now Lee-Carter Model)
Generalized Additive Forecasting Mortality
State-space models for statistical mortality projections
Mortality Modelling using Generalized Estimating Equations
Modelling and forecasting age-at-death distributions
Age-Gender-Country-Specific Death Rates Modelling and Forecasting: A Linear Mixed-Effects Model
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