Updating functional demographic models and coherent functional demographic models.

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.

Usage

# S3 method for class 'fmforecast'
update(object, ...)

# S3 method for class 'fmforecast2'
update(object, ...)

Arguments

object

Output from either fdm or coherentfdm.

...

Extra arguments currently ignored.

Value

A list of the same class as object.

See also

forecast.fdm, forecast.fdmpr

Author

Rob J Hyndman.

Examples

if (FALSE) { # \dontrun{
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)
} # }