Description Usage Arguments Value Author(s) See Also Examples
Returns forecasts and other information for univariate ETS models.
1 2 3 4 |
object |
An object of class " |
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 |
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. |
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 |
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) |
Rob J Hyndman
1 2 | fit <- ets(USAccDeaths)
plot(forecast(fit,h=48))
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.