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, jumpchoice = c("fit", "actual"), method =
"arima", warnings=FALSE, ...)
Object of class fmforecast with the following components:
labelName of region from which the data are taken.
ageAges from lcaout object.
yearYears from lcaout object.
rateList 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.
errorMatrix of one-step errors for historical data
fittedMatrix of one-step forecasts for historical data
coeffList of objects of type forecast containing the coefficients and their forecasts.
coeff.errorOne-step errors for each of the coefficients.
varList containing the various components of variance: model, error, mean, total and coeff.
modelFitted model in obj.
typeType of data: mortality, fertility or migration.