ilc: matflc.plot – R documentation

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matflc.plot

Miscellaneous plotting functions for lca and lca.rh type regression objects. Plot of forecasted Lee-Carter models based on a series of fitted model objects

Description

Comparison plots of the forecasted period effect and life expectancy of a series of fitted Lee-Carter models

Usage

matflc.plot(lca.obj, lca.base, at = 65, label = NULL, ...)

Arguments

`lca.obj`	a list of fitted model objects of class `lca` (such as returned by `elca.rh` function)
`lca.base`	base fitted model object of class `lca` to be used in comparison
`at`	target age at which to calculate life expectancy
`label`	a data label
`...`	additional arguments to `forecast` function

Details

The function makes use of a univariate ARIMA process (i.e. random walk with drift) in order to extrapolate the period effects k_t of the model objects in lca.obj, which is illustrated by the calendar years together with the corresponding forecasted life expectancy for a given age.

Value

Plot

Author(s)

Z. Butt and S. Haberman and H. L. Shang

Examples

rfp.cmi <- dd.rfp(dd.cmi.pens, c(0.5, 1.2, -0.7, 2.5))
mod6e <- elca.rh(rfp.cmi, age=50:70, interpolate=TRUE, dec=3)
# plot with original (fitted) base values
matflc.plot(mod6e$lca, label='RFP CMI')
# use a standard LC model fitting as base values
mod6 <- lca.rh(dd.cmi.pens, mod='lc', error='gauss', max.age = 70, interpolate=TRUE)
matflc.plot(mod6e$lca, mod6, label='RFP CMI')

ilc

Lee-Carter Mortality Models using Iterative Fitting Algorithms

v1.0

GPL (>= 2)

Authors

Zoltan Butt, Steven Haberman and Han Lin Shang

Initial release

2014-11-19