inst/unitTests/runit.garchFit.init.R

# This library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Library General Public
# License as published by the Free Software Foundation; either
# version 2 of the License, or (at your option) any later version.
#
# This library is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Library General Public License for more details.
#
# You should have received a copy of the GNU Library General
# Public License along with this library; if not, write to the
# Free Foundation, Inc., 59 Temple Place, Suite 330, Boston,
# MA  02111-1307  USA

# Copyrights (C)
# for this R-port:
#   1999 - 2008, Diethelm Wuertz, Rmetrics Foundation, GPL
#   Diethelm Wuertz <[email protected]>
#   [email protected]
#   www.rmetrics.org
# for the code accessed (or partly included) from other R-ports:
#   see R's copyright and license files
# for the code accessed (or partly included) from contributed R-ports
# and other sources
#   see Rmetrics's copyright file


################################################################################
# FUNCTION:               PARAMETER ESTIMATION:
#  'fGARCH'                S4: fGARCH Class representation
#  garchFit                Fits GARCH and APARCH processes
################################################################################


test.garchFit.init <-
    function()
{
    # RVs:
    RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
    set.seed(4711, kind = "Marsaglia-Multicarry")

    # Simulate Garch(1,1) Series:
    x = garchSim(n = 250)

    # Modify Start Values - mci default:
    fit = garchFit( ~ garch(1,1), x, init.rec = "mci", trace = FALSE) # default
    print(coef(fit))

    # Modify Start Values - uev alternative:
    # fit = garchFit( ~ garch(1,1), x, init.rec = "uev", trace = FALSE)
    # Error in .garchFit(formula.mean = args$formula.mean, formula.var = args$formula.var,  :
    #   Algorithm only supported for mci Recursion
    # coef(fit)

    # Return Value:
    return()
}


################################################################################

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fGarch documentation built on Nov. 17, 2017, 2:15 p.m.