Nothing
# 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 <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
################################################################################
test.plot.methods1 <-
function()
{
# Load data:
data(dem2gbp)
dem2gbp = as.vector(dem2gbp[, 1])
# Fit to normal Conditional Distribution:
fit = garchFit( ~ garch(1, 1), data = dem2gbp, trace = FALSE)
print(fit)
# garchFit 1:
# 1:
# 2:
# Graph Frame:
par(mfrow = c(2, 1))
# Plot 1:
plot(fit, which = 1)
mtext("norm-GARCH(1,1) Modeling", line = 0.5, cex = 0.8)
mtext("DEM2GBP Data Vector", side = 4, adj = 0, cex = 0.7, col = "darkgrey")
# Plot 2:
plot(fit, which = 2)
mtext("norm-GARCH(1,1) Modeling", line = 0.5, cex = 0.8)
mtext("DEM2GBP Data Vector", side = 4, adj = 0, cex = 0.7, col = "darkgrey")
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.plot.methods2 <-
function()
{
# Load data:
data(dem2gbp)
# Fit to normal Conditional Distribution:
fit = garchFit( ~ garch(1, 1), data = dem2gbp, trace = FALSE)
print(fit)
# garchFit 2:
# Graph Frame:
par(mfrow = c(1, 1))
# Plot 3:
plot(fit, which = 3)
mtext("norm-GARCH(1,1) Modeling", line = 0.5, cex = 0.8)
mtext("DEM2GBP Data Vector", side = 4, adj = 0, cex = 0.7,
col = "darkgrey")
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.plot.methods3 <-
function()
{
# Load data:
data(dem2gbp)
# Fit to normal Conditional Distribution:
fit = garchFit( ~ garch(1, 1), data = dem2gbp, trace = FALSE)
print(fit)
# garchFit3:
# 3:
# 4:
# 5:
# Graph Frame:
par(mfrow = c(2, 1))
# Plot 4:
plot(fit, which = 4)
mtext("norm-GARCH(1,1) Modeling", line = 0.5, cex = 0.8)
mtext("DEM2GBP Data Vector", side = 4, adj = 0, cex = 0.7,
col = "darkgrey")
# Plot 5:
plot(fit, which = 5)
mtext("norm-GARCH(1,1) Modeling", line = 0.5, cex = 0.8)
mtext("DEM2GBP Data Vector", side = 4, adj = 0, cex = 0.7,
col = "darkgrey")
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.plot.methods4 <-
function()
{
# Load data:
data(dem2gbp)
# Fit to normal Conditional Distribution:
fit = garchFit( ~ garch(1, 1), data = dem2gbp, trace = FALSE)
print(fit)
# garchFit4:
# 6: Cross Correlation
# 7: Residuals
# 8: Conditional SDs
# 9: Standardized Residuals
# Graph Frame:
par(mfrow = c(2, 2))
# Plot 6:
plot(fit, which = 6)
mtext("norm-GARCH(1,1) Modeling", line = 0.5, cex = 0.8)
mtext("DEM2GBP Data Vector", side = 4, adj = 0, cex = 0.7,
col = "darkgrey")
# Plot 7:
plot(fit, which = 7)
mtext("norm-GARCH(1,1) Modeling", line = 0.5, cex = 0.8)
mtext("DEM2GBP Data Vector", side = 4, adj = 0, cex = 0.7,
col = "darkgrey")
# Plot 8:
plot(fit, which = 8)
mtext("norm-GARCH(1,1) Modeling", line = 0.5, cex = 0.8)
mtext("DEM2GBP Data Vector", side = 4, adj = 0, cex = 0.7,
col = "darkgrey")
# Plot 9:
plot(fit, which = 9)
mtext("norm-GARCH(1,1) Modeling", line = 0.5, cex = 0.8)
mtext("DEM2GBP Data Vector", side = 4, adj = 0, cex = 0.7,
col = "darkgrey")
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.plot.methods5 <-
function()
{
# Load data:
data(dem2gbp)
# Fit to normal Conditional Distribution:
fit = garchFit( ~ garch(1, 1), data = dem2gbp, trace = FALSE)
print(fit)
# garchFit5:
# 10: ACF of Standardized Residuals
# 11: ACF of Squared Standardized Residuals
# 12: Cross Correlation between r^2 and r
# 13: QQ-Plot of Standardized Residuals
# Graph Frame:
par(mfrow = c(2, 2))
# Plot 10:
plot(fit, which = 10)
mtext("norm-GARCH(1,1) Modeling", line = 0.5, cex = 0.8)
mtext("DEM2GBP Data Vector", side = 4, adj = 0, cex = 0.7,
col = "darkgrey")
# Plot 11:
plot(fit, which = 11)
mtext("norm-GARCH(1,1) Modeling", line = 0.5, cex = 0.8)
mtext("DEM2GBP Data Vector", side = 4, adj = 0, cex = 0.7,
col = "darkgrey")
# Plot 12:
plot(fit, which = 12)
mtext("norm-GARCH(1,1) Modeling", line = 0.5, cex = 0.8)
mtext("DEM2GBP Data Vector", side = 4, adj = 0, cex = 0.7,
col = "darkgrey")
# Plot 13:
plot(fit, which = 13)
mtext("norm-GARCH(1,1) Modeling", line = 0.5, cex = 0.8)
mtext("DEM2GBP Data Vector", side = 4, adj = 0, cex = 0.7,
col = "darkgrey")
# Return Value:
return()
}
################################################################################
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.