emanuelealiverti / dysm

Dynamic modeling of mortality via mixtures of skewed distribution

Dynamic modeling of mortality via mixtures of skewed distribution functions [dysm]

This repository is associated with the paper: Aliverti, Mazzuco, Scarpa (2021). Dynamic modeling of mortality via mixtures of skewed distribution functions.

It contains code implementing the method and to reproduce the main results of the papers.

1. download_data/ contains instruction on how to download the data from Human Mortality Database. Users need to be registered and provide their credentials in the script download_data/get_data.R. The registration is free and generally validated in few hours.

2. APPLICATION/ contains the main code implementing the method, the c++ utilities related to the Owen-T function and Skew-Normal distribution, and instructions on how to reproduce results from the paper (such as the figure reported below).

   • In order to reproduce the results, it is necessary to download the data at point 1, and run APPLICATION/00_Run_PostInference.r for the male and female populations and save the MCMC sample (100k iterations require approximately 3hours).
   • The script compile automatically the internal c++ utilities, creating a compiled APPLICATION/skew_cdf.o, which is internally linked to nimble MCMC. (check APPLICATION/nimble_model_integral.r)
   • The script APPLICATION/01_PlotResults.r loads the MCMC sample, computes forecasts, and reproduce the figure below.