life.expectancy: Estimate life expectancy from mortality rates

Description

All three functions estimate life expectancy from lifetable. The function flife.expectancy is primarily designed for forecast life expectancies and will optionally produce prediction intervals. Where appropriate, it will package the results as a forecast object which makes it much easier to product nice plots of forecast life expectancies. The e0 function is a shorthand wrapper for flife.expectancy with age=0.

Usage

life.expectancy(
  data,
  series = names(data$rate)[1],
  years = data$year,
  type = c("period", "cohort"),
  age = min(data$age),
  max.age = min(100, max(data$age))
)
flife.expectancy(
  data,
  series = NULL,
  years = data$year,
  type = c("period", "cohort"),
  age,
  max.age = NULL,
  PI = FALSE,
  nsim = 500,
  ...
)
e0(
  data,
  series = NULL,
  years = data$year,
  type = c("period", "cohort"),
  max.age = NULL,
  PI = FALSE,
  nsim = 500,
  ...
)

Value

Time series of life expectancies (one per year), or a forecast object of life expectancies (one per year).

Arguments

data: Demogdata object of type “mortality” such as obtained from read.demogdata, or an object of class fmforecast such as the output from forecast.fdm or forecast.lca, or an object of class fmforecast2 such as the output from forecast.fdmpr.
series: Name of mortality series to use. Default is the first demogdata series in data.
years: Vector indicating which years to use.
type: Either period or cohort.
age: Age at which life expectancy is to be calculated.
max.age: Maximum age for life table calculation.
PI: If TRUE, produce a prediction interval.
nsim: Number of simulations to use when computing a prediction interval.
...: Other arguments passed to simulate when producing prediction intervals.

Author

Rob J Hyndman

Examples

Run this code

plot(life.expectancy(fr.mort), ylab = "Life expectancy")

france.LC <- lca(fr.mort, adjust = "e0", years = 1950:1997)
france.fcast <- forecast(france.LC, jumpchoice = "actual")
france.e0.f <- life.expectancy(france.fcast)

france.fdm <- fdm(extract.years(fr.mort, years = 1950:2006))
france.fcast <- forecast(france.fdm)
if (FALSE) {
e0.fcast <- e0(france.fcast, PI = TRUE, nsim = 200)
plot(e0.fcast)
}

life.expectancy(fr.mort, type = "cohort", age = 50)