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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: GEV SIMULATION:
# gevSim Simulates a GEV distributed process
# gumbelSim Simulates a Gumbel distributed process
################################################################################
gevSim =
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 GEV distribution
# Arguments:
# Examples:
# gevSim(n = 100)
# gevSim(n = 100, seed = 4711)
# gevSim(model = list(xi = -0.15, mu = 0, beta = 0.02))
# FUNCTION:
# Seed:
if (is.null(seed)) seed = NA else set.seed(seed)
# Simulate:
ans = rgev(n = n, xi = model$xi, mu = model$mu, beta = model$beta)
# DW: ans = as.ts(ans)
ans = timeSeries(ans, units = "GEV")
# Control:
attr(ans, "control") =
data.frame(t(unlist(model)), seed = seed, row.names = "control")
# Return Value:
ans
}
# ------------------------------------------------------------------------------
gumbelSim =
function(model = list(mu = 0, beta = 1), n = 1000, seed = NULL)
{ # A function implemented by Diethelm Wuertz
# Description:
# Generates random variates from a GEV distribution
# Arguments:
# Examples:
# gumbelSim(n = 100)
# gumbelSim(n = 100, seed = 4711)
# FUNCTION:
# Simulate:
ans = gevSim(model = list(xi = 0, mu = model$mu, beta = model$beta),
n = n, seed = seed)
colnames(ans) = "GUMBEL"
# Return Value:
ans
}
################################################################################
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