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. 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:

modelA list containing information about the
fitted model

methodThe name of the forecasting method as a
character string

meanPoint forecasts as a time series

lowerLower limits for prediction intervals

upperUpper
limits for prediction intervals

levelThe confidence values
associated with the prediction intervals

xThe original time series
(either `object`

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

).

residualsResiduals 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.

fittedFitted values (one-step forecasts)

## See also

`ets`

, `ses`

, `holt`

,
`hw`

.

## Examples