splinef

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Cubic Spline Forecast

Returns local linear forecasts and prediction intervals using cubic smoothing splines.

Keywords
ts
Usage
splinef(x, h=10, level=c(80,95), fan=FALSE, lambda=NULL)
Arguments
x
a numeric vector or time series
h
Number of periods for forecasting
level
Confidence level for prediction intervals.
fan
If TRUE, level is set to seq(50,99,by=1). This is suitable for fan plots.
lambda
Box-Cox transformation parameter. Ignored if NULL. Otherwise, forecasts back-transformed via an inverse Box-Cox transformation.
Details

The cubic smoothing spline model is equivalent to an ARIMA(0,2,2) model but with a restricted parameter space. The advantage of the spline model over the full ARIMA model is that it provides a smooth historical trend as well as a linear forecast function. Hyndman, King, Pitrun, and Billah (2002) show that the forecast performance of the method is hardly affected by the restricted parameter space.

Value

  • An object of class "forecast".

    The function summary is used to obtain and print a summary of the results, while the function plot produces a plot of the forecasts and prediction intervals.

    The generic accessor functions fitted.values and residuals extract useful features of the value returned by meanf.

    An object of class "forecast" is a list containing at least the following elements:

  • modelA list containing information about the fitted model
  • methodThe name of the forecasting method as a character string
  • meanPoint forecasts as a time series
  • lowerLower limits for prediction intervals
  • upperUpper limits for prediction intervals
  • levelThe confidence values associated with the prediction intervals
  • xThe original time series (either object itself or the time series used to create the model stored as object).
  • residualsResiduals from the fitted model. That is x minus fitted values.
  • fittedFitted values (one-step forecasts)

References

Hyndman, King, Pitrun and Billah (2005) Local linear forecasts using cubic smoothing splines. Australian and New Zealand Journal of Statistics, 47(1), 87-99. http://robjhyndman.com/papers/splinefcast/.

See Also

smooth.spline, arima, holt.

Aliases
  • splinef
Examples
fcast <- splinef(uspop,h=5)
plot(fcast)
summary(fcast)
Documentation reproduced from package forecast, version 3.24, License: GPL (>= 2)

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