| rwf {forecast} | R Documentation |
Returns forecasts and prediction intervals for a random walk with drift model applied to x.
rwf(x, h=10, drift=FALSE, level=c(80,95), fan=FALSE, lambda=NULL)
x |
a numeric vector or time series |
h |
Number of periods for forecasting |
drift |
Logical flag. If TRUE, fits a random walk with drift model. |
level |
Confidence levels 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. |
The random walk with drift model is
Y[t]=c + Y[t-1] + Z[t]
where Z[t] is a normal iid error. Forecasts are given by
Y[n+h]=ch+Y[n]
. If there is no drift, the drift parameter c=0. Forecast standard errors allow for uncertainty in estimating the drift parameter.
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 |
residuals |
Residuals from the fitted model. That is x minus fitted values. |
fitted |
Fitted values (one-step forecasts) |
Rob J Hyndman
gold.fcast <- rwf(gold[1:60],h=50) plot(gold.fcast)