mpascariu / coda

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

Compositional Data Mortality Model (CoDa) - R Package

This package has retired

The CoDa package has been deprecated and is no longer under development. Its functionalities and improved methods have been included into the MortalityForecast package.

Description

This repository contains the implementation of the Compositional Data Mortality Model (CoDa). This is a Lee-Carter (1992) type method that is used to modelling and forecasting the life table distribution of deaths (dx) using Principal Component Analysis. In the context of mortality forecasting the CoDa method was fist used in Bergeron-Boucher et al. (2017). The package includes functions for fitting the model, analysing it's goodness-of-fit and performing mortality projections.

Help

All functions are documented in the standard way, which means that once you load the package using library(CoDa) you can just type ?coda to see the help file.

References

Bergeron-Boucher, M-P., Canudas-Romo, V., Oeppen, J. and Vaupel, W.J. 2017. Coherent forecasts of mortality with compositional data analysis. Demographic Research, Volume 17, Article 17, Pages 527--566.

Oeppen, J. 2008. Coherent forecasting of multiple-decrement life tables: A test using Japanese cause of death data. Paper presented at the European Population Conference 2008, Barcelona, Spain, July 9-12, 2008.

Aitchison, J. 1986. The Statistical Analysis of Compositional Data. London: Chapman and Hall. 2015.

Ronald D. Lee and Lawrence R. Carter. 1992. Modeling and Forecasting U.S. Mortality, Journal of the American Statistical Association, 87:419, 659--671.

Wikipedia. Compositional data