isfe.fts: Integrated Squared Forecast Error for models of various orders

Description

Computes integrated squared forecast error (ISFE) values for functional time series models of various orders.

Usage

isfe.fts(data, max.order = N - 3, N = 10, h = 5:10, method = 
 c("classical", "M", "rapca"), mean = TRUE, level = FALSE, 
  fmethod = c("arima", "ar", "ets", "ets.na", "struct", "rwdrift", 
   "rw", "arfima"), lambda = 3, ...)

Value

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

Arguments

data: An object of class fts.
max.order: Maximum number of principal components to fit.
N: Minimum number of functional observations to be used in fitting a model.
h: Forecast horizons over which to average.
method: Method to use for principal components decomposition. Possibilities are “M”, “rapca” and “classical”.
mean: Indicates if mean term should be included.
level: Indicates if level term should be included.
fmethod: Method used for forecasting. Current possibilities are “ets”, “arima”, “ets.na”, “struct”, “rwdrift” and “rw”.
lambda: Tuning parameter for robustness when method = "M".
...: Additional arguments controlling the fitting procedure.

Author

Rob J Hyndman

References