demography (version 1.13)

forecast.fdm: Forecast functional demographic model.

Description

The coefficients from the fitted object are forecast using a univariate time series model. The forecast coefficients are then multiplied by the basis functions to obtain a forecast demographic rate curve.

Usage

## S3 method for class 'fdm':
forecast(object, h = 50, level=80, jumpchoice = c("fit", "actual"), method =
				 "arima", warnings=FALSE, ...)

Arguments

object

Output from fdm.

h

Forecast horizon.

level

Confidence level for prediction intervals.

jumpchoice

If "actual", the forecasts are bias-adjusted by the difference between the fit and the last year of observed data. Otherwise, no adjustment is used.

method

Forecasting method to be used.

warnings

If TRUE, warnings arising from the forecast models for coefficients will be shown. Most of these can be ignored, so the default is warnings=FALSE.

...

Other arguments as for forecast.ftsm.

Value

• Object of class fmforecast with the following components:
• label
  Name of region from which the data are taken.
• age
  Ages from lcaout object.
• year
  Years from lcaout object.
• rate
  List of matrices containing forecasts, lower bound and upper bound of prediction intervals. Point forecast matrix takes the same name as the series that has been forecast.
• error
  Matrix of one-step errors for historical data
• fitted
  Matrix of one-step forecasts for historical data
• coeff
  List of objects of type forecast containing the coefficients and their forecasts.
• coeff.error
  One-step errors for each of the coefficients.
• var
  List containing the various components of variance: model, error, mean, total and coeff.
• model
  Fitted model in obj.
• type
  Type of data: mortality, fertility or migration.

See Also

fdm, forecast.lca, forecast.ftsm.

Examples

france.fit <- fdm(fr.mort,order=2)
france.fcast <- forecast(france.fit,50)
plot(france.fcast)
models(france.fcast)