simulate: Simulation from a time series model

In ttnsdcn/forecast-package: Forecasting functions for time series

Description

Returns a time series based on the model object object.

Usage

## S3 method for class 'ets'
simulate(object, nsim=length(object$x), seed=NULL, future=TRUE, 
    bootstrap=FALSE, ...)
## S3 method for class 'ar'
simulate(object, nsim=object$n.used, seed=NULL, future=TRUE, 
    bootstrap=FALSE, ...)
## S3 method for class 'Arima'
simulate(object, nsim=length(object$x), seed=NULL, xreg=NULL, future=TRUE, 
    bootstrap=FALSE, ...)
## S3 method for class 'fracdiff'
simulate(object, nsim=object$n, seed=NULL, future=TRUE, 
    bootstrap=FALSE, ...)

Arguments

object	An object of class "ets", "Arima" or "ar".
nsim	Number of periods for the simulated series
seed	Either NULL or an integer that will be used in a call to set.seed before simulating the time series. The default, NULL will not change the random generator state.
future	Produce sample paths that are future to and conditional on the data in object.
bootstrap	If TRUE, simulation uses resampled errors rather than normally distributed errors.
xreg	New values of xreg to be used for forecasting. Must have nsim rows.
...	Other arguments.

Value

An object of class "ts".

Author(s)

Rob J Hyndman

See Also

ets, Arima, auto.arima, ar, arfima.

Examples

fit <- ets(USAccDeaths)
plot(USAccDeaths,xlim=c(1973,1982))
lines(simulate(fit, 36),col="red")

ttnsdcn/forecast-package documentation built on June 1, 2019, 2:49 a.m.