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Computes ISFE values for functional time series models of various orders.

Usage

isfe(...)

# S3 method for demogdata
isfe(
  data,
  series = names(data$rate)[1],
  max.order = N - 3,
  N = 10,
  h = 5:10,
  ages = data$age,
  max.age = max(ages),
  method = c("classical", "M", "rapca"),
  fmethod = c("arima", "ar", "arfima", "ets", "ets.na", "struct", "rwdrift", "rw"),
  lambda = 3,
  ...
)

Arguments

...

Additional arguments control the fitting procedure.

data

demogdata object.

series

name of series within data holding rates (1x1)

max.order

Maximum number of basis functions to fit.

N

Minimum number of functional observations to be used in fitting a model.

h

Forecast horizons over which to average.

ages

Ages to include in fit.

max.age

Maximum age to fit.

method

Method to use for principal components decomposition. Possibilities are “M”, “rapca” and “classical”.

fmethod

Method used for forecasting. Current possibilities are “ets”, “arima”, “ets.na”, “struct”, “rwdrift” and “rw”.

lambda

Tuning parameter for robustness when method="M".

Value

Numeric matrix with (max.order+1) rows and length(h) columns containing ISFE values for models of orders 0:max.order.

References

Hyndman, R.J., and Ullah, S. (2007) Robust forecasting of mortality and fertility rates: a functional data approach. Computational Statistics & Data Analysis, 51, 4942-4956. https://robjhyndman.com/publications/funcfor/

See also

Author

Rob J Hyndman