arima.sim {stats} R Documentation

## Simulate from an ARIMA Model

### Description

Simulate from an ARIMA model.

### Usage

```arima.sim(model, n, rand.gen = rnorm, innov = rand.gen(n, ...),
n.start = NA, ...)
```

### Arguments

 `model` A list with component `ar` and/or `ma` giving the AR and MA coefficients respectively. Optionally a component `order` can be used. An empty list gives an ARIMA(0, 0, 0) model, that is white noise. `n` length of output series, before un-differencing. `rand.gen` optional: a function to generate the innovations. `innov` an optional times series of innovations. If not provided, `rand.gen` is used. `n.start` length of “burn-in” period. If `NA`, the default, a reasonable value is computed. `...` additional arguments for `rand.gen`. Most usefully, the standard deviation of the innovations generated by `rnorm` can be specified by `sd`.

### Details

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.

### Value

A time-series object of class `"ts"`.

`arima`

### Examples

```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)
```

[Package stats version 2.1.0 Index]