# forecast.ets

##### Forecasting using ETS models

Returns forecasts and other information for univariate ETS models.

- Keywords
- ts

##### Usage

```
# 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. 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. By default, the value is taken from what was used when fitting the model.

- ...
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:

A list containing information about the fitted model

The name of the forecasting method as a character string

Point forecasts as a time series

Lower limits for prediction intervals

Upper limits for prediction intervals

The confidence values associated with the prediction intervals

The original time series
(either `object`

itself or the time series used to create the model
stored as `object`

).

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 values (one-step forecasts)

##### See Also

##### Examples

```
# NOT RUN {
fit <- ets(USAccDeaths)
plot(forecast(fit,h=48))
# }
```

*Documentation reproduced from package forecast, version 8.1, License: GPL (>= 3)*