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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: ELLIPTICAL COPULAE PARAMETER FITTING:
# ellipticalCopulaSim Simulates bivariate elliptical copula
# ellipticalCopulaFit Fits the paramter of an elliptical copula
################################################################################
test.copulaSim =
function()
{
# Arguments:
# ellipticalCopulaSim(n, rho = 0.75, param = NULL,
# type = c("norm", "cauchy", "t"))
# Normal Copula:
rho = 0.5
R = ellipticalCopulaSim(n = 1000, rho = rho)
R[1:10, ]
plot(R, pch = 19)
# Cauchy Copula:
rho = runif(1, -1, 1)
R = ellipticalCopulaSim(n = 100, rho = rho, type = "cauchy")
R[1:10, ]
plot(R, pch = 19)
# Student-t Copula:
rho = runif(1, -1, 1)
nu = runif(1, 3, 20)
print(c(rho, nu))
R = ellipticalCopulaSim(n = 1000, rho = rho, param = nu, type = "t")
R[1:10, ]
plot(R, pch = 19)
# The remaining Copulae are not yet implemented ...
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.copulaFit =
function()
{
# Arguments:
# ellipticalCopulaFit(u, v = NULL, type = c("norm", "cauchy", "t"), ...)
# Fit Normal Copula:
rho = 0.5
R = ellipticalCopulaSim(n = 1000, rho = rho)
fit = ellipticalCopulaFit(u = R[,1], v = R[,2])
fit
rho - fit$par
plot(c(-1,1), c(-1,1), xlab = "rho", ylab = "estimate", main = "Normal")
for ( i in 1:100) {
rho = runif(1, -1, 1)
R = ellipticalCopulaSim(n = 1000, rho = rho)
fit = ellipticalCopulaFit(R)
points(rho, fit$par)
print(c(rho-fit$par, fit$Rho-fit$par))
}
# Fit Cauchy Copula:
rho = runif(1, -1, 1)
R = ellipticalCopulaSim(n = 100, rho = rho, type = "cauchy")
ellipticalCopulaFit(R, type = "cauchy")
rho
plot(c(-1,1), c(-1,1), main = "Cauchy")
for ( i in 1:100) {
rho = runif(1, -1, 1)
R = ellipticalCopulaSim(n = 1000, rho = rho, type = "cauchy")
fit = ellipticalCopulaFit(R, type = "cauchy")
points(rho, fit$par)
print(c(rho-fit$par, fit$Rho-fit$par))
}
# Fit Student-t Copula:
rho = runif(1, -1, 1)
nu = runif(1, 3, 20)
print(c(rho, nu))
R = ellipticalCopulaSim(n = 1000, rho = rho, param = nu, type = "t")
ellipticalCopulaFit(R, type = "t")
plot(c(-1,1), c(-1,1), main = "Student-t")
for ( i in 1:100) {
rho = runif(1, -1, 1)
nu = runif(1, 3, 20)
R = ellipticalCopulaSim(n = 1000, rho = rho, param = nu, type = "t")
fit = ellipticalCopulaFit(R, type = "t")
points(rho, fit$par[1])
print(c(rho, nu, fit$par))
}
# The remaining Copulae are not yet implemented ...
# Return Value:
return()
}
################################################################################
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