In mpascariu/MortalityGaps: The Double-Gap Life Expectancy Forecasting Model

This package contains source code for the Double-Gap model for forecasting life expectancy in human populations.

Description

Life expectancy is highly correlated over time among countries and between males and females. These associations can be used to improve forecasts. Here we have implemented a method for forecasting female life expectancy based on analysis of the gap between female life expectancy in a country compared with the record level of female life expectancy in the world. Second, to forecast male life expectancy, the gap between male life expectancy and female life expectancy in a country is analysed. We named this method the Double-Gap model. For a detailed description of the method see Pascariu et al. (2017).

Installation

1. Make sure you have the most recent version of R
2. Run the following code in your R console

install.packages("MortalityGaps")

Updating to the latest version of the package

You can track and contribute to the development of MortalityGaps on GitHub. To install it:

1. Install the release version of devtools from CRAN with install.packages("devtools").

2. Make sure you have a working development environment.

   • Windows: Install Rtools.
   • Mac: Install Xcode from the Mac App Store.
   • Linux: Install a compiler and various development libraries (details vary across different flavors of Linux).

3. Install the development version of MortalityGaps.

R devtools::install_github("mpascariu/MortalityGaps")

Help

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

Examples

library(MortalityGaps)

Input data

# Collection of life expectancies for female populations
exF <- MortalityGaps.data$exF
# Life expectancy for male populations
exM <- MortalityGaps.data$exM

head(exF)

Fit DG model at age 0 for Australia using data from 1950 to 2014

M0 <- DoubleGap(DF = exF,
                DM = exM,
                age = 0,
                country = "AUS",
                years = 1950:2014)
M0

Summary results

summary(M0)

Forecast life expectancy in Australia until 2050

P0 <- predict(M0, h = 36)

Plot the results

plot(P0)

mpascariu/MortalityGaps documentation built on May 7, 2021, 1:45 p.m.