mT.extrapolateProbsExp: Extrapolate base table of a mortalityTable using an...

In kainhofer/r-mortality-tables: A Framework for Various Types of Mortality / Life Tables

Description

Extrapolate the base table of a mortalityTable object using an exponential function (i.e. the death probabilities decreases towards 0 exponentially). While death probabilities trending towards 0 for old ages is not realistic for overall deaths, it can be useful to model causes of death that vanish in older age. It is, however, most useful to extrapolate an observed base table to low ages (e.g. for an insurance portfolio with practically no persons aged below 16). A decline towards 0 for low ages makes sense in this case.

Usage

mT.extrapolateProbsExp(table, age, up = TRUE)

Arguments

table	A life table object (instance of a mortalityTable class) or a list, table or array of mortalityTable objects
age	Index (typically age) of the position of the fit
up	Whether the fit is forward- or backward-facing (i.e. to old or young ages)

Details

The function needs only one age, from which the extrapolation using an exponential function is applied. the strength of the exponential function is derived from the death probability at that age.

Examples

mortalityTables.load("Austria_Census")
# use the Austrian population mortalities for ages 18-95 and exponentially
# extrapolate them to lower ages
AT11.lowAgesExp = mT.extrapolateProbsExp(mort.AT.census.2011.male, 18, up = FALSE)
plotMortalityTables(mT.setName(AT11.lowAgesExp, "Ages below 16 are extrapolated exponentially"),
                    mort.AT.census.2011.male)

kainhofer/r-mortality-tables documentation built on Dec. 17, 2020, 3:53 a.m.