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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: GEV DISTRIBUTION FAMILY: [CALLING EVD]
# dgev Density for the GEV Distribution
# pgev Probability for the GEV Distribution
# qgev Quantiles for the GEV Distribution
# rgev Random variates for the GEV Distribution
# gevMoments Computes true statistics for GEV distribution
# gevSlider Displays distribution and rvs for GEV distribution
################################################################################
test.gev =
function()
{
# Check Distribution:
RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
set.seed(4711, kind = "Marsaglia-Multicarry")
distCheck(fun = "gev", n = 2000, xi = 0.0, mu = 0, beta = 1)
# Check Distribution:
RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
set.seed(4711, kind = "Marsaglia-Multicarry")
distCheck(fun = "gev", n = 5000, xi = 0.3, mu = 0, beta = 2)
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.gevMoments =
function()
{
# gevMoments(xi = 0, mu = 0, beta = 1)
# Compute Moments:
xi = seq(-4.5, 1.5, by = 0.25)
mom = gevMoments(xi)
print(mom)
# Plot Mean:
par(mfrow = c(2, 1), cex = 0.7)
par(ask = FALSE)
xi = seq(-5, 2, length = 351)
mom = gevMoments(xi)
plot(xi, mom$mean, main = "Mean GEV", pch = 19, col = "steelblue")
abline(v = 1, col = "red", lty = 3)
abline(h = 0, col = "red", lty = 3)
# Plot Variance:
plot(xi, log(mom$var), main = "log Variance GEV", pch = 19, col = "steelblue")
abline(v = 1/2, col = "red", lty = 3)
abline(h = 0.0, col = "red", lty = 3)
# check gevMoments for specific values
xi <- c(-1, 0, 0.3)
mu <- c(-1, 0, 1)
beta <- c(0.5, 1, 10)
for (i in seq(length(xi))) {
for (j in seq(length(xi))) {
for (k in seq(length(xi))) {
rg <- rgev(1000000, xi = xi[i], mu = mu[j], beta = beta[k])
rgMoments <- gevMoments(xi = xi[i], mu = mu[j], beta = beta[k])
checkEqualsNumeric(mean(rg), rgMoments$mean, tolerance = 0.1)
checkEqualsNumeric(var(rg), rgMoments$var, tolerance = 0.1)
}
}
}
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.gevSlider =
function()
{
# Distribution Slider:
# print("Activate Slider manually!")
# gevSlider(method = "dist")
NA
# Random Variates Slider:
# print("Activate Slider manually!")
# gevSlider(method = "rvs")
NA
# Return Value:
return()
}
################################################################################
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