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(), ...)
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 skewnormal distribution, “std” for the studentt, “sstd” for the skewstudentt, “ged” for the generalized error distribution, “sged” for the skewgeneralized 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.
.
A '>ARFIMAspec
object containing details of the ARFIMA specification.
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 