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

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Description

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

Usage

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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

See Also

matfle.plot, flc.plot, elca.rh

Examples

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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')

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