Forecast mortality using Compositional Data Lee-Carter model - R Package

Standard tools to compare and evaluate mortality forecasting methods

Modelling and forecasting cohort mortality

Project for the Bayesian Statistics exam at University of Trieste

The Double-Gap Life Expectancy Forecasting Model - R Package

Improved Mortality Forecasts using Artificial Intelligence.

Lee Carter model and different cross-validation methods for mortality forecasting models, implemented in Python.

R package - Computing mortality rates from tobacco and alcohol related causes. This is a mirror of the code in the private Gitlab repository

Generalized Additive Forecasting Mortality

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

State-space models for statistical mortality projections

Mortality Modelling using Generalized Estimating Equations

Modelling and forecasting adult age-at-death distributions

Modelling and forecasting age-at-death distributions

Python implementations of different mortality modeling techniques (for now Lee-Carter Model)

Mortality rate predictions for Italy in 2020 using Lee-Carter model and Recurrent Neural Networks

Age-Gender-Country-Specific Death Rates Modelling and Forecasting: A Linear Mixed-Effects Model