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