# matfle.plot: Miscellaneous plotting functions for 'lca' and 'lca.rh' type... In ilc: Lee-Carter Mortality Models using Iterative Fitting Algorithms

## Description

Compute the historical and forecasted life expectancy of a series of fitted Lee-Carter models and plot them in one comparative figure

## Usage

 `1` ```matfle.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

It makes use of the `life.expectancy` and `forecast` functions from the `demography` and `forecast` packages, respectively, in order to compute life expectancy at the specified target age for each of the model objects in `lca.obj`.

Plot

## Author(s)

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

`matflc.plot`, `fle.plot`, `elca.rh`
 ```1 2 3 4 5 6 7``` ```rfp.cmi <- dd.rfp(dd.cmi.pens, c(0.5, 1.2, -0.7, 2.5)) mod6e <- elca.rh(rfp.cmi, age=50:100, interpolate=TRUE, dec=3) # plot with original (fitted) base values matfle.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', interpolate=TRUE) matfle.plot(mod6e\$lca, mod6, label='RFP CMI') ```