`lca`

and `lca.rh`

type regression objects.
Plot of forecasted life expectancy based on a series of fitted Lee-Carter model objects
Compute the historical and forecasted life expectancy of a series of fitted Lee-Carter models and plot them in one comparative figure

1 | ```
matfle.plot(lca.obj, lca.base, at = 65, label = NULL, ...)
``` |

`lca.obj` |
a list of fitted model objects of class |

`lca.base` |
base fitted model object of class |

`at` |
target age at which to calculate life expectancy |

`label` |
a data label |

`...` |
additional arguments to |

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

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')
``` |

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