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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
# Copyrights (C)
# for this R-port:
# 1999 - 2007, Diethelm Wuertz, GPL
# Diethelm Wuertz <wuertz@itp.phys.ethz.ch>
# info@rmetrics.org
# 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: ARCHIMEDEAN COPULAE RANDOM VARIATES:
# rarchmCopula Generates Archimedean copula random variates
# rarchmSlider Displays interactively archimedean probability
# FUNCTION: ARCHIMEDEAN COPULAE PROBABILITY:
# parchmCopula Computes Archimedean copula probability
# parchmSlider Displays interactively archimedean probability
# FUNCTION: ARCHIMEDEAN COPULAE DENSITY:
# darchmCopula Computes Archimedean copula density
# darchmSlider Displays interactively archimedean density
# FUNCTION: SPECIAL BIVARIATE COPULA:
# rgumbelCopula Generates fast gumbel random variates
# pgumbelCopula Computes bivariate Gumbel copula probability
# dgumbelCopula Computes bivariate Gumbel copula density
################################################################################
test.rarchmCopula =
function()
{
# Arguments:
# rarchmCopula(n, alpha = NULL, type = archmList())
# Random Variates - Check all Types:
for (type in archmList()) {
R = rarchmCopula(n = 5, alpha = NULL, type = type)
cat("\n")
print(type)
print(R)
}
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.rarchmSlider =
function()
{
# Arguments:
# rarchmSlider(B = 10)
# Try Slider:
# rarchmSlider()
NA
# Return Value:
return()
}
################################################################################
test.parchmCopula =
function()
{
# Arguments:
# parchmCopula(u = 0.5, v = u, alpha = NULL, type = archmList(),
# output = c("vector", "list"), alternative = FALSE)
# u - single input value:
parchmCopula()
parchmCopula(0.5)
parchmCopula(0.5, 0.25)
# u - input vector:
U = (0:10)/10
V = U
parchmCopula(U)
parchmCopula(u = U, v = V)
parchmCopula(u = U, v = rev(V))
# u - input matrix:
parchmCopula(cbind(U, V))
# u - input list:
u = grid2d()
u
parchmCopula(u) # output = "vector"
parchmCopula(u, output = "list")
diff = parchmCopula(u) - parchmCopula(u, alternative = TRUE)
mean(abs(diff))
# Check All Types:
u = grid2d()
for (type in paste(1:22)) {
cop1 = parchmCopula(u, type = type, output = "list")
cop2 = parchmCopula(u, type = type, output = "list", alternative = TRUE)
cat("Type: ", type, "\t Difference: ", mean(abs(cop1$z-cop2$z)), "\n")
persp(cop1, main = type, theta = -40, phi = 30, col = "steelblue")
}
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.parchmSlider =
function()
{
# Arguments:
# parchmSlider(type = c("persp", "contour"), B = 10)
# Try Perspective Slider:
# parchmSlider()
NA
# Try Contour Slider:
# parchmSlider("contour")
NA
# Return Value:
return()
}
################################################################################
test.darchmCopula =
function()
{
# Arguments:
# darchmCopula(u = 0.5, v = u, alpha = NULL, type = archmList(),
# output = c("vector", "list"), alternative = FALSE)
# u - single input value:
darchmCopula()
darchmCopula(0.5)
darchmCopula(0.5, 0.25)
# u - input vector:
U = (0:10)/10
V = U
darchmCopula(U)
darchmCopula(u = U, v = V)
darchmCopula(u = U, v = rev(V))
# u - input matrix:
darchmCopula(cbind(U, V))
# u - input list:
u = grid2d()
u
darchmCopula(u) # output = "vector"
darchmCopula(u, output = "list")
# Check All Types:
u = grid2d(x = (0:25)/25)
for (type in archmList()) {
cop1 = darchmCopula(u, type = type, output = "list")
cop2 = darchmCopula(u, type = type, output = "list",
alternative = TRUE)
diff = abs(cop1$z-cop2$z)
diff = diff[!is.na(diff)]
cat("Type: ", type, "\t Difference: ", mean(diff), "\n")
persp(cop2, main = type, theta = -40, phi = 30, col = "steelblue")
}
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.darchmSlider =
function()
{
# Arguments:
# darchmSlider(type = c("persp", "contour"), B = 10)
# Try Perspective Slider:
# darchmSlider()
NA
# Try Contour Slider:
# darchmSlider("contour")
NA
# Return Value:
return()
}
################################################################################
test.rgumbelCopula =
function()
{
# Generates fast gumbel random variates
# Copula:
rgumbelCopula()
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.pgumbelCopula =
function()
{
# Computes bivariate Gumbel copula probability
# Copula:
pgumbelCopula()
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.dgumbelCopula =
function()
{
# Computes bivariate Gumbel copula density
# Copula:
dgumbelCopula()
# Return Value:
return()
}
################################################################################
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