lARFIMAwTF: Exact log-likelihood of a long memory model with a transfer...
In JQVeenstra/arfima: Fractional ARIMA (and Other Long Memory) Time Series Modeling

lARFIMAwTF

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 `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.