CoDa: Fit CoDa Mortality Model

In mpascariu/CoDa: Compositional-Data Lee-Carter Mortality Model (CoDa)

Description

Fit Compositional Data (CoDa) model for forecasting the life table distribution of deaths. CoDa is a Lee-Carter type model. A key difference between the Lee-Carter (1992) method and the Compositional Data (CoDa) model is that the former fits and forecasts the death rates (mx) while the latter is based on the life table death distribution (dx). See Bergeron-Boucher et al. (2017) for a detail description and mathematical formulation.

Usage

coda(data, x = NULL, y = NULL)

Arguments

data	Matrix containing mortality data (dx) with ages as row and time as column.
x	Vector of input ages (optional). Used to label the output objects and plots.
y	Vector of input years (optional). Used to label the output objects and plots.

Value

The output is an object of class "coda" with the components:

input	List with arguments provided in input. Saved for convenience.
call	An unevaluated function call, that is, an unevaluated expression which consists of the named function applied to the given arguments.
coefficients	Estimated coefficients.
fitted.values	Fitted values of the estimated CoDa model.
residuals	Deviance residuals.
x	Vector of ages used in the fitting.
y	Vector of years used in the fitting.

References

1. 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.

2. 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.

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

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

See Also

predict.coda

Examples

# Fit CoDa model
M <- coda(CoDa.data)
summary(M)

# Forecast life expectancy
P <- predict(M, h = 20)

mpascariu/CoDa documentation built on May 5, 2019, 7 p.m.