mlt {MortCast}

Model Life Tables Mortality Patterns

Description

Predict age-specific mortality rates using Coale-Demeny and UN model life tables.

Usage

mlt(e0, sex = c("male", "female"), type = "CD_West", nx = 5, ...)

mltj(e0m, e0f, ..., nx = 5)

Arguments

e0

A time series of target life expectancy.

sex

Either "male" or "female".

type

Type of the model life table. Available options are “CD_East”, “CD_North”, “CD_South”, “CD_West”, “UN_Chilean”, “UN_Far_Eastern”, “UN_General”, “UN_Latin_American”, “UN_South_Asian”.

nx

Size of age groups. Should be either 5 or 1.

...

Additional arguments passed to the underlying function.

e0m

A time series of target male life expectancy.

e0f

A time series of target female life expectancy.

Details

Given a level of life expectancy (e0), sex and a type of model life table, the function extracts the corresponding mortality pattern from MLTlookup (for abridged LT) or MLT1Ylookup (for 1-year LT), while interpolating between neighboring e0 groups. Function mlt is for one sex, while mltj can be used for both sexes.

Value

Function mlt returns a matrix with the predicted mortality rates. Columns correspond to the values in the e0 vector and rows correspond to age groups. Function mltj returns a list of such matrices, one for each sex.

References

https://www.un.org/development/desa/pd/data/extended-model-life-tables

Coale, A., P. Demeny, and B. Vaughn. 1983. Regional model life tables and stable populations. 2nd ed. New York: Academic Press.

See Also

mortcast, mortcast.blend, pmd, MLTlookup

Examples

data(e0Fproj, package = "wpp2017")
country <- "Uganda"
# get target e0
e0f <- subset(e0Fproj, name == country)[-(1:2)]
# project into future using life table Cole-Demeny North
mx <- mlt(e0f, sex = "female", type = "CD_North")
# plot first projection in black and the remaining ones in grey 
plot(mx[,1], type = "l", log = "y", ylim = range(mx),
    ylab = "female mx", xlab = "Age", 
    main = paste(country, "5-year age groups"))
for(i in 2:ncol(mx)) lines(mx[,i], col = "grey")

# MLT for 1-year age groups
mx1y <- mlt(e0f, sex = "female", type = "CD_North", nx = 1)
plot(mx1y[,1], type = "l", log = "y", ylim = range(mx1y),
    ylab = "female mx", xlab = "Age", 
    main = paste(country, "1-year age groups"))
for(i in 2:ncol(mx1y)) lines(mx1y[,i], col = "grey")