Returns forecasts and other information for univariate ETS models.

```
# S3 method for ets
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 = NULL,
...
)
```

## Arguments

- 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 are produced by simulation rather
than using analytic formulae. Errors are assumed to be normally distributed.

- bootstrap
If TRUE, then prediction intervals are produced by simulation using
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. If `lambda="auto"`

,
then a transformation is automatically selected using `BoxCox.lambda`

.
The transformation is ignored if NULL. Otherwise,
data transformed before model is estimated.

- biasadj
Use adjusted back-transformed mean for Box-Cox
transformations. If transformed data is used to produce forecasts and fitted values,
a regular back transformation will result in median forecasts. If biasadj is TRUE,
an adjustment will be made to produce mean forecasts and fitted values.

- ...
Other arguments.

## 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 `forecast.ets`

.

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.
For models with additive errors, the residuals are x - fitted values. For
models with multiplicative errors, the residuals are equal to x /(fitted
values) - 1.

- fitted
Fitted values (one-step forecasts)