`update.fmforecast()`

updates `fdm`

forecasts. The argument `object`

is the output from `forecast.fdm`

which has been subsequently modified with new coefficient forecasts. These new forecasts are used when re-calculating the forecast of the mortality or fertility rates, or net migration numbers.

`update.fmforecast2()`

updates `fdmpr`

forecasts. The argument `object`

is the output from `forecast.fdmpr`

which has been subsequently modified with new coefficient forecasts.

1 2 3 4 |

`object` |
Output from either |

`...` |
Extra arguments currently ignored. |

A list of the same class as `object`

.

Rob J Hyndman.

`forecast.fdm`

, `forecast.fdmpr`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
## Not run:
france.fit <- fdm(fr.mort,order=2)
france.fcast <- forecast(france.fit,50)
# Replace first coefficient model with ARIMA(0,1,2)+drift
france.fcast$coeff[[2]] <- forecast(Arima(france.fit$coeff[,2],
order=c(0,1,2), include.drift=TRUE), h=50, level=80)
france.fcast <- update(france.fcast)
fr.short <- extract.years(fr.sm,1950:2006)
fr.fit <- coherentfdm(fr.short)
fr.fcast <- forecast(fr.fit)
par(mfrow=c(1,2))
plot(fr.fcast$male)
# Replace first coefficient model in product component with a damped ETS model:
fr.fcast$product$coeff[[2]] <- forecast(ets(fr.fit$product$coeff[,2], damped=TRUE),
h=50, level=80)
fr.fcast <- update(fr.fcast)
plot(fr.fcast$male)
## End(Not run)
``` |

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