Generates a time series from an AR(\(p\)) model. The parent Gaussian process is constructed to match a target autocorrelation structure via the Yule-Walker equations, then transformed to a target marginal distribution and optional intermittency (probability of zeros).
ARp(margdist, margarg, acsvalue, actfpara, n, p = NULL, p0 = 0)A numeric vector of length n with the following attributes:
Target marginal distribution name.
Target marginal distribution parameters.
Original (untransformed) target ACS.
Probability of zeros.
AR(\(p\)) coefficients (Yule-Walker solution).
Standard deviation of the Gaussian innovations.
The underlying Gaussian process (length n).
ACTF-transformed ACS used for the AR model.
Character. Name of the target marginal distribution
(e.g. "ggamma", "paretoII"). Must have a quantile function
q<margdist> available.
Named list. Parameters of the marginal distribution passed
to q<margdist>.
Numeric vector. Target autocorrelation structure starting
from lag 0 (i.e. acsvalue[1] = 1).
List returned by fitactf, containing the
fitted ACTF coefficients in actfpara$actfcoef.
Positive integer. Length of the generated time series.
Positive integer or NULL. AR model order. When
NULL (default), the order is chosen automatically as the number of
lags where the transformed ACS exceeds 0.01, capped at 1000.
Numeric in \([0, 1)\). Probability of zero values
(intermittency). Default 0.
generateTS, actpnts,
fitactf, acs