lARFIMAwTF: 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
)

Value

A log-likelihood value

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 arima.
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 arima.
dfs: The seasonal fractional differencing parameter.
H: The Hurst parameter for fractional Gaussian noise (FGN). Should not be mixed with dfrac or alpha: see "Details".
Hs: The Hurst parameter for seasonal fractional Gaussian noise (FGN). Should not be mixed with dfs or alphas: see "Details".
alpha: The decay parameter for power-law autocovariance (PLA) noise. Should not be mixed with dfrac or H: see "Details".
alphas: The decay parameter for seasonal power-law autocovariance (PLA) noise. Should not be mixed with dfs or Hs: see "Details".
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.

Author

Justin Veenstra

References

Veenstra, J.Q. Persistence and Antipersistence: Theory and Software (PhD Thesis)