RW() returns a random walk model, which is equivalent to an ARIMA(0,1,0) model with an optional drift coefficient included using drift(). naive() is simply a wrapper to rwf() for simplicity. snaive() returns forecasts and prediction intervals from an ARIMA(0,0,0)(0,1,0)m model where m is the seasonal period.

RW(formula, ...)

NAIVE(formula, ...)

SNAIVE(formula, ...)

## Arguments

formula Model specification (see "Specials" section). Not used.

## Value

A model specification.

## 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 (as in naive), the drift parameter c=0. Forecast standard errors allow for uncertainty in estimating the drift parameter (unlike the corresponding forecasts obtained by fitting an ARIMA model directly).

The seasonal naive model is $$Y_t= Y_{t-m} + Z_t$$ where $$Z_t$$ is a normal iid error.

## Specials

### lag

The lag special is used to specify the lag order for the random walk process. If left out, this special will automatically be included.

lag(lag = NULL)

 lag The lag order for the random walk process. If lag = m, forecasts will return the observation from m time periods ago. This can also be provided as text indicating the duration of the lag window (for example, annual seasonal lags would be "1 year").

### drift

The drift special can be used to include a drift/trend component into the model. By default, drift is not included unless drift() is included in the formula.

drift(drift = TRUE)

 drift If drift = TRUE, a drift term will be included in the model.

## Examples

library(tsibbledata)
aus_production %>%
model(rw = RW(Beer ~ drift()))
#> # A mable: 1 x 1
#>              rw
#>         <model>
#> 1 <RW w/ drift>
as_tsibble(Nile) %>%
model(NAIVE(value))
#> # A mable: 1 x 1
#>   NAIVE(value)
#>          <model>
#> 1        <NAIVE>library(tsibbledata)
aus_production %>%
model(snaive = SNAIVE(Beer ~ lag("year")))
#> # A mable: 1 x 1
#>     snaive
#>    <model>
#> 1 <SNAIVE>