forecast.ets | R Documentation |
Returns forecasts and other information for univariate ETS models.
## S3 method for class '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,
...
)
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. If |
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. |
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
ets
, ses
, holt
,
hw
.
fit <- ets(USAccDeaths)
plot(forecast(fit,h=48))
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