thetaf: Theta method forecast

In forecast: Forecasting Functions for Time Series and Linear Models

Theta method forecast

Description

Returns forecasts and prediction intervals for a theta method forecast.

Usage

thetaf(
  y,
  h = ifelse(frequency(y) > 1, 2 * frequency(y), 10),
  level = c(80, 95),
  fan = FALSE,
  x = y
)

Arguments

y	a numeric vector or time series of class ts
h	Number of periods for forecasting
level	Confidence levels for prediction intervals.
fan	If TRUE, level is set to seq(51,99,by=3). This is suitable for fan plots.
x	Deprecated. Included for backwards compatibility.

Details

The theta method of Assimakopoulos and Nikolopoulos (2000) is equivalent to simple exponential smoothing with drift. This is demonstrated in Hyndman and Billah (2003).

The series is tested for seasonality using the test outlined in A&N. If deemed seasonal, the series is seasonally adjusted using a classical multiplicative decomposition before applying the theta method. The resulting forecasts are then reseasonalized.

Prediction intervals are computed using the underlying state space model.

More general theta methods are available in the forecTheta package.

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 rwf.

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

model	A list containing information about the fitted model
method	The name of the forecasting method as a character string
mean	Point forecasts as a time series
lower	Lower limits for prediction intervals
upper	Upper limits for prediction intervals
level	The confidence values associated with the prediction intervals
x	The original time series (either object itself or the time series used to create the model stored as object).
residuals	Residuals from the fitted model. That is x minus fitted values.
fitted	Fitted values (one-step forecasts)

Author(s)

Rob J Hyndman

References

Assimakopoulos, V. and Nikolopoulos, K. (2000). The theta model: a decomposition approach to forecasting. International Journal of Forecasting 16, 521-530.

Hyndman, R.J., and Billah, B. (2003) Unmasking the Theta method. International J. Forecasting, 19, 287-290.

See Also

arima, meanf, rwf, ses

Examples

nile.fcast <- thetaf(Nile)
plot(nile.fcast)

forecast documentation built on June 22, 2024, 9:20 a.m.