forecast.lca {demography}

Forecast demogdata data using Lee-Carter method.

Description

The kt coefficients are forecast using a random walk with drift. The forecast coefficients are then multiplied by bx to obtain a forecast demographic rate curve.

Usage

## S3 method for class 'lca'
forecast(
  object,
  h = 50,
  se = c("innovdrift", "innovonly"),
  jumpchoice = c("fit", "actual"),
  level = 80,
  ...
)

Arguments

object

Output from lca.

h

Number of years ahead to forecast.

se

Method used for computation of standard error. Possibilities: “innovdrift” (innovations and drift) and “innovonly” (innovations only).

jumpchoice

Method used for computation of jumpchoice. Possibilities: “actual” (use actual rates from final year) and “fit” (use fitted rates).

level

Confidence level for prediction intervals.

...

Other arguments.

Value

Object of class fmforecast with the following components:

label

Region from which the data are taken.

age

Ages from object.

year

Years from 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.

fitted

Matrix of one-step forecasts for historical data

Other components included are

e0

Forecasts of life expectancies (including lower and upper bounds)

kt.f

Forecasts of coefficients from the model.

type

Data type.

model

Details about the fitted model

Author(s)

Rob J Hyndman

See Also

lca, plot.fmforecast

Examples

france.lca <- lca(fr.mort, adjust="e0")
france.fcast <- forecast(france.lca, 50)
plot(france.fcast)
plot(france.fcast,'c')