Method for creating an ARFIMA specification object prior to fitting.
arfimaspec(mean.model = list(armaOrder = c(1, 1), include.mean = TRUE,
arfima = FALSE, external.regressors = NULL), distribution.model = "norm",
start.pars = list(), fixed.pars = list(), ...)A ARFIMAspec object containing details of the ARFIMA specification.
List containing the mean model specification:
armaOrder The autoregressive (ar) and moving average (ma) orders (if any).
include.mean Whether to include the mean.
arfima Whether to include arfima (0<d<0.5).
external.regressors A matrix object containing the external regressors to
include in the mean equation with as many rows as will be included in the
data (which is passed in the fit function).
The distribution density to use for the innovations. Valid choices are “norm” for the normal distibution, “snorm” for the skew-normal distribution, “std” for the student-t, “sstd” for the skew-student-t, “ged” for the generalized error distribution, “sged” for the skew-generalized error distribution, “nig” for the normal inverse gaussian distribution, “ghyp” for the Generalized Hyperbolic, and “jsu” for Johnson's SU distribution. Note that some of the distributions are taken from the fBasics package and implenented locally here for convenience. The “jsu” distribution is the reparametrized version from the “gamlss” package.
List of staring parameters for the optimization routine. These are not usually required unless the optimization has problems converging.
List of parameters which are to be kept fixed during the optimization. It is
possible that you designate all parameters as fixed so as to quickly recover just
the results of some previous work or published work. The optional argument
“fixed.se” in the arfimafit function indicates whether to
calculate standard errors for those parameters fixed during the post optimization
stage.
.
Alexios Ghalanos
The specification allows for flexibility in ARFIMA modelling.
In order to understand which parameters can be entered in the start.pars and
fixed.pars optional arguments, the list below exposes the names used for the
parameters:(note that when a parameter is followed by a number, this represents
the order of the model. Just increment the number for higher orders):
Mean Model:
| constant | mu | |
| AR term | ar1 | |
| MA term | ma1 | |
| exogenous regressors | mxreg1 | |
| arfima | arfima |
Distribution Model:
| dlambda | dlambda (for GHYP distribution) | |
| skew | skew | |
| shape | shape |