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 fdm
forecast(
  object,
  h = 50,
  level = 80,
  jumpchoice = c("fit", "actual"),
  method = "arima",
  warnings = FALSE,
  ...
)

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”.

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.

Author

Rob J Hyndman

Examples

Run this code

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