R: Simulate fractional ARIMA Time Series

fracdiff.sim {fracdiff}

R Documentation

Simulate fractional ARIMA Time Series

Description

Generates simulated long-memory time series data from the fractional ARIMA(p,d,q) model. This is a test problem generator for fracdiff.

Usage

fracdiff.sim(n, ar = NULL, ma = NULL, d,
             rand.gen = rnorm, innov = rand.gen(n+q, ...),
             n.start = NA, allow.0.nstart = FALSE, ..., mu = 0.)

Arguments

`n`	length of the time series.
`ar`	vector of autoregressive parameters; empty by default.
`ma`	vector of moving average parameters; empty by default.
`d`	fractional differencing parameter.
`rand.gen`	a function to generate the innovations; the default, `rnorm` generates white N(0,1) noise.
`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, the same value as in `arima.sim` is computed.
`allow.0.nstart`	logical indicating if `n.start = 0` should be allowed even when p + q > 0. This not recommended unless for producing the same series as with older versions of `fracdiff.sim`.
`...`	additional arguments for `rand.gen()`. Most usefully, the standard deviation of the innovations generated by `rnorm` can be specified by `sd`.
`mu`	time series mean (added at the end).

Value

a list containing the following elements :

`series`	time series
`ar, ma, d, mu, n.start`	same as input

Examples

## Pretty (too) short to "see" the long memory
fracdiff.sim(100, ar = .2, ma = .4, d = .3)

## longer with "extreme" ar:
r <- fracdiff.sim(n=1500, ar=-0.9, d= 0.3)
plot(as.ts(r$series))