Description Usage Arguments Details Value Author(s) See Also Examples
Returns a time series based on the model object object
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ## S3 method for class 'ets'
simulate(object, nsim=length(object$x), seed=NULL, future=TRUE,
bootstrap=FALSE, innov=NULL, ...)
## S3 method for class 'ar'
simulate(object, nsim=object$n.used, seed=NULL, future=TRUE,
bootstrap=FALSE, innov=NULL, ...)
## S3 method for class 'Arima'
simulate(object, nsim=length(object$x), seed=NULL, xreg=NULL, future=TRUE,
bootstrap=FALSE, innov=NULL, lambda=object$lambda, ...)
## S3 method for class 'fracdiff'
simulate(object, nsim=object$n, seed=NULL, future=TRUE,
bootstrap=FALSE, innov=NULL, ...)
## S3 method for class 'nnetar'
simulate(object, nsim=length(object$x), seed=NULL, xreg=NULL, future=TRUE,
bootstrap=FALSE, innov=NULL, lambda=object$lambda, ...)
|
object |
An object of class " |
nsim |
Number of periods for the simulated series. Ignored if either |
seed |
Either |
future |
Produce sample paths that are future to and conditional on the data in |
bootstrap |
Do simulation using resampled errors rather than normally distributed errors or errors provided as |
innov |
A vector of innovations to use as the error series. Ignored if |
xreg |
New values of |
lambda |
Box-Cox parameter. If not |
... |
Other arguments, not currently used. |
With simulate.Arima()
, the object
should be produced by Arima
or auto.arima
, rather than arima
. By default, the error series is assumed normally distributed and generated using rnorm
. If innov
is present, it is used instead. If bootstrap=TRUE
and innov=NULL
, the residuals are resampled instead.
When future=TRUE
, the sample paths are conditional on the data. When future=FALSE
and the model is stationary, the sample paths do not depend on the data at all. When future=FALSE
and the model is non-stationary, the location of the sample paths is arbitrary, so they all start at the value of the first observation.
An object of class "ts
".
Rob J Hyndman
ets
, Arima
, auto.arima
, ar
, arfima
, nnetar
.
1 2 3 | fit <- ets(USAccDeaths)
plot(USAccDeaths, xlim=c(1973,1982))
lines(simulate(fit, 36), col="red")
|
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