lARFIMAwTF {arfima} | R Documentation |
Exact log-likelihood of a long memory model with a transfer function model and series included Computes the exact log-likelihood of a long memory model with respect to a given time series as well as a transfer fucntion model and series. This function is not meant to be used directly.
Description
Once again, this function should not be used externally.
Usage
lARFIMAwTF(
z,
phi = numeric(0),
theta = numeric(0),
dfrac = numeric(0),
phiseas = numeric(0),
thetaseas = numeric(0),
dfs = numeric(0),
H = numeric(0),
Hs = numeric(0),
alpha = numeric(0),
alphas = numeric(0),
xr = numeric(0),
r = numeric(0),
s = numeric(0),
b = numeric(0),
delta = numeric(0),
omega = numeric(0),
period = 0,
useC = 3,
meanval = 0
)
Arguments
z |
A vector or (univariate) time series object, assumed to be (weakly) stationary. |
phi |
The autoregressive parameters in vector form. |
theta |
The moving average parameters in vector form. See Details for
differences from |
dfrac |
The fractional differencing parameter. |
phiseas |
The seasonal autoregressive parameters in vector form. |
thetaseas |
The seasonal moving average parameters in vector form. See
Details for differences from |
dfs |
The seasonal fractional differencing parameter. |
H |
The Hurst parameter for fractional Gaussian noise (FGN). Should
not be mixed with |
Hs |
The Hurst parameter for seasonal fractional Gaussian noise (FGN).
Should not be mixed with |
alpha |
The decay parameter for power-law autocovariance (PLA) noise.
Should not be mixed with |
alphas |
The decay parameter for seasonal power-law autocovariance
(PLA) noise. Should not be mixed with |
xr |
The regressors in vector form |
r |
The order of the delta(s) |
s |
The order of the omegas(s) |
b |
The backshifting to be done |
delta |
Transfer function parameters as in Box, Jenkins, and Reinsel. Corresponds to the "autoregressive" part of the dynamic regression. |
omega |
Transfer function parameters as in Box, Jenkins, and Reinsel. Corresponds to the "moving average" part of the dynamic regression: note that omega_0 is not restricted to 1. See "Details" for issues. |
period |
The periodicity of the seasonal components. Must be >= 2. |
useC |
How much interfaced C code to use: an integer between 0 and 3. The value 3 is strongly recommended. See "Details". |
meanval |
If the mean is to be estimated dynamically, the mean. |
Value
A log-likelihood value
Author(s)
Justin Veenstra
References
Veenstra, J.Q. Persistence and Antipersistence: Theory and Software (PhD Thesis)