arfimaspec-methods: function: ARFIMA Specification

In rugarch: Univariate GARCH Models

function: ARFIMA Specification

Description

Method for creating an ARFIMA specification object prior to fitting.

Usage

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(), ...) 

Arguments

mean.model	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).
distribution.model	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.
start.pars	List of staring parameters for the optimization routine. These are not usually required unless the optimization has problems converging.
fixed.pars	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.
...	.

Details

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

Value

A ARFIMAspec object containing details of the ARFIMA specification.

Author(s)

Alexios Ghalanos

rugarch documentation built on Sept. 30, 2024, 9:30 a.m.