forecast
is a generic function for forecasting from time series or
time series models. The function invokes particular methods which
depend on the class of the first argument.
# S3 method for ts
forecast(
object,
h = ifelse(frequency(object) > 1, 2 * frequency(object), 10),
level = c(80, 95),
fan = FALSE,
robust = FALSE,
lambda = NULL,
biasadj = FALSE,
find.frequency = FALSE,
allow.multiplicative.trend = FALSE,
model = NULL,
...
)# S3 method for default
forecast(object, ...)
# S3 method for forecast
print(x, ...)
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 accessors functions fitted.values
and residuals
extract various useful features of the value returned by
forecast$model
.
An object of class "forecast"
is a list usually 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 will be x minus the fitted values.
Fitted values (one-step forecasts)
a time series or time series model for which forecasts are required
Number of periods for forecasting
Confidence level for prediction intervals.
If TRUE, level
is set to seq(51,99,by=3)
. This is
suitable for fan plots.
If TRUE, the function is robust to missing values and outliers
in object
. This argument is only valid when object
is of class
ts
.
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.
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.
If TRUE, the function determines the appropriate period, if the data is of unknown period.
If TRUE, then ETS models with multiplicative trends are allowed. Otherwise, only additive or no trend ETS models are permitted.
An object describing a time series model; e.g., one of of class
ets
, Arima
, bats
, tbats
, or nnetar
.
Additional arguments affecting the forecasts produced. If
model=NULL
, forecast.ts
passes these to ets
or
stlf
depending on the frequency of the time series. If
model
is not NULL
, the arguments are passed to the relevant
modelling function.
a numeric vector or time series of class ts
.
Rob J Hyndman
For example, the function forecast.Arima
makes forecasts based
on the results produced by arima
.
If model=NULL
,the function forecast.ts
makes forecasts
using ets
models (if the data are non-seasonal or the seasonal
period is 12 or less) or stlf
(if the seasonal period is 13 or
more).
If model
is not NULL
, forecast.ts
will apply the
model
to the object
time series, and then generate forecasts
accordingly.
Other functions which return objects of class "forecast"
are
forecast.ets
, forecast.Arima
,
forecast.HoltWinters
, forecast.StructTS
,
meanf
, rwf
, splinef
,
thetaf
, croston
, ses
,
holt
, hw
.
WWWusage %>% forecast %>% plot
fit <- ets(window(WWWusage, end=60))
fc <- forecast(WWWusage, model=fit)
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