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# 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
################################################################################
# FUNCTION: GPD SIMULATION:
# gpdSim Simulates a GPD distributed process
################################################################################
gpdSim =
function(model = list(xi = 0.25, mu = 0, beta = 1), n = 1000, seed = NULL)
{
# A function implemented by Diethelm Wuertz
# Description:
# Generates random variates from a GPD distribution
# Arguments:
# model - a list of model parameters, xi, mu and beta.
# n - an integer, the number of simulated random variates
# seed - an integer, the random number generator seed
# FUNCTION:
# Seed:
if (is.null(seed)) seed = NA else set.seed(seed)
# Simulate:
ans = rgpd(n = n, xi = model$xi, mu = model$mu, beta = model$beta)
# DW: ans = as.ts(ans)
ans = timeSeries(ans, units = "GPD")
# Control:
attr(ans, "control") =
data.frame(t(unlist(model)), seed = seed, row.names = "")
# Return Value:
ans
}
################################################################################
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