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”.