| kannisto.predict {MortCast} | R Documentation |
Kannisto Prediction
Description
Given estimated Kannisto parameters (coherent or original), it predicts mortality rates for given ages.
Usage
kannisto.predict(pars, ages)
Arguments
pars |
A named vector with Kanisto coefficients |
ages |
A vector of ages to make prediction for. These can be indices of age groups or raw ages, but on the same scale as used in the estimation. |
Details
Given parameters c and d in pars,
the function uses the Kannisto equation logit(m_x) = \log(c) + dx,
to predict mortality rates for age groups x given by ages.
Value
Vector of predicted mortality rates.
References
Thatcher, A. R., Kannisto, V. and Vaupel, J. W. (1998). The Force of Mortality at Ages 80 to 120, volume 5 of Odense Monographs on Population Aging Series. Odense, Denmark: Odense University Press.
See Also
cokannisto, kannisto.estimate, cokannisto.estimate
Examples
data(mxM, mxF, package = "wpp2017")
mxm <- subset(mxM, name == "Germany")[,"2010-2015"]
ages <- c(0, 1, seq(5, 130, by=5))
# using original Kannisto parameters
pars <- kannisto.estimate(mxm[18:21], ages = ages[18:21])
mxm.pred <- kannisto.predict(pars$coefficients, ages = ages[22:28])
plot(ages, c(mxm[1:21], mxm.pred), type="l", log="y",
xlab="age", ylab="mx")
# Coherent Kannisto
mxf <- subset(mxF, name == "Germany")[,"2010-2015"]
copars <- cokannisto.estimate(
mxm[18:21], mxf[18:21], ages = ages[18:21])
cmxm.pred <- kannisto.predict(copars[["male"]]$coefficients, ages = ages[22:28])
cmxf.pred <- kannisto.predict(copars[["female"]]$coefficients, ages = ages[22:28])
plot(ages, c(mxm[1:21], cmxm.pred), type="l", log="y",
xlab="age", ylab="mx", col="blue")
lines(ages, c(mxf[1:21], cmxf.pred), col="red")