`"forecast"(object, h=ifelse(object$m>1, 2*object$m, 10), level=c(80,95), fan=FALSE, simulate=FALSE, bootstrap=FALSE, npaths=5000, PI=TRUE, lambda=object$lambda, biasadj=FALSE, ...)`

object

An object of class "

`ets`

". Usually the result of a call to `ets`

.h

Number of periods for forecasting

level

Confidence level for prediction intervals.

fan

If TRUE, level is set to seq(51,99,by=3). This is suitable for fan plots.

simulate

If TRUE, prediction intervals produced by simulation rather than using analytic formulae.

bootstrap

If TRUE, and if

`simulate=TRUE`

, then simulation uses resampled errors rather than normally distributed
errors.npaths

Number of sample paths used in computing simulated prediction intervals.

PI

If TRUE, prediction intervals are produced, otherwise only point forecasts are calculated. If

`PI`

is FALSE, then `level`

, `fan`

, `simulate`

, `bootstrap`

and `npaths`

are all ignored.lambda

Box-Cox transformation parameter. Ignored if NULL. Otherwise, forecasts back-transformed via an inverse Box-Cox transformation.

biasadj

Use adjusted back-transformed mean for Box-Cox transformations. If TRUE, point forecasts and fitted values are mean forecast. Otherwise, these points can be considered the median of the forecast densities.

...

Other arguments.

`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 `forecast.ets`

.An object of class `"forecast"`

is a list containing at least the following elements:
is a list containing at least the following elements:`ets`

, `ses`

, `holt`

, `hw`

.```
plot(forecast(fit,h=48))
```

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