# rwf

From forecast v2.19
by Rob Hyndman

##### Random Walk Forecast

Returns forecasts and prediction intervals for a random walk with drift model applied to x.

- Keywords
- ts

##### Usage

`rwf(x, h=10, drift=FALSE, level=c(80,95), fan=FALSE)`

##### Arguments

- 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.

##### Details

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.

##### 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)

##### See Also

##### Examples

```
gold.fcast <- rwf(gold[1:60],h=50)
plot(gold.fcast)
```

*Documentation reproduced from package forecast, version 2.19, License: GPL (>= 2)*

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