`arima`

or `estimate`

function.
`forecast(object, lead = 1, id = NULL, alpha = 0.05, output = TRUE)`

object

the result of an

`arima`

or `estimate`

fit.lead

the number of steps ahead for which prediction is required. The default is

`1`

.id

the id of the observation which is the time. The default is

`NULL`

.alpha

the significant level for constructing the confidence interval of prediction.
The default is

`0.05`

.output

a logical value indicating to print the results in R console.
The default is

`TRUE`

.-
A matrix with

`lead`

rows and five columns. Each column represents the number
of steps ahead (`Lead`

), the predicted values (`Forecast`

), the standard errors
(`S.E`

) and the 100*(1 - $\alpha$)% lower bound (`Lower`

) and upper bound
(`Upper`

) of confidence interval.
`predict.Arima`

in `stats`

package,
but has a nice output
including 100*(1 - $\alpha$)% confidence interval and a prediction plot. It is
similar to FORECAST statement in PROC ARIMA of SAS.
`predict.Arima`

x <- arima.sim(list(order = c(3,0,0),ar = c(0.2,0.4,-0.15)),n = 100) fit <- estimate(x,p = 3) # same as fit <- arima(x,order = c(3,0,0)) forecast(fit,lead = 4) # forecast with id t <- as.Date("2014-03-25") + 1:100 forecast(fit,lead = 4, id = t)