# 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. 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:

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 8.9, License: GPL-3*