arima.fracdiff.sim(model, n = 10000)
d
,
ar
,
ma
,
mu
, where
d
is the fractional differencing parameter (0 < d < .5).
Default is 0.25
ar
is the vector of autoregressive parameters.
Default is NULL
ma
is the vector of moving average parameters.
Default is NULL
mu
is the time series mean. Default is 0
model
and random number seed as attributes.
Haslett, J. and Raftery, A. E.(1989).
Space-time modeling with long-memory dependence:
assessing Ireland's wind power resource (with discussion).
Applied Statistics
38, 1-50.
The chapter "Analyzing Time Series" of the S-PLUS Guide to Statistical and Mathematical Analysis.
# generate a fractionally-differenced ARIMA(1,d,1) model # given initial values arima.fracdiff.sim(model = list(d = .3, ar = .2, ma = .4), n = 1000)