| arima.sim | R Documentation |
Simulate from an ARIMA model.
arima.sim(model, n, rand.gen = rnorm, innov = rand.gen(n, ...),
n.start = NA, start.innov = rand.gen(n.start, ...),
...)
model |
A list with component |
n |
length of output series, before un-differencing. A strictly positive integer. |
rand.gen |
optional: a function to generate the innovations. |
innov |
an optional times series of innovations. If not
provided, |
n.start |
length of ‘burn-in’ period. If |
start.innov |
an optional times series of innovations to be used
for the burn-in period. If supplied there must be at least
|
... |
additional arguments for |
See arima for the precise definition of an ARIMA model.
The ARMA model is checked for stationarity.
ARIMA models are specified via the order component of
model, in the same way as for arima. Other
aspects of the order component are ignored, but inconsistent
specifications of the MA and AR orders are detected. The
un-differencing assumes previous values of zero, and to remind the
user of this, those values are returned.
Random inputs for the ‘burn-in’ period are generated by calling
rand.gen.
A time-series object of class "ts".
arima
require(graphics)
arima.sim(n = 63, list(ar = c(0.8897, -0.4858), ma = c(-0.2279, 0.2488)),
sd = sqrt(0.1796))
# mildly long-tailed
arima.sim(n = 63, list(ar = c(0.8897, -0.4858), ma = c(-0.2279, 0.2488)),
rand.gen = function(n, ...) sqrt(0.1796) * rt(n, df = 5))
# An ARIMA simulation
ts.sim <- arima.sim(list(order = c(1,1,0), ar = 0.7), n = 200)
ts.plot(ts.sim)
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