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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 - 2006, 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: DESCRIPTION:
# dgh Returns density for generalized hyperbolic DF
# pgh Returns probability for generalized hyperbolic DF
# qgh Returns quantiles for generalized hyperbolic DF
# rgh Returns random variates for generalized hyperbolic DF
# FUNCTION: DESCRIPTION:
# dhyp Returns density for hyperbolic DF
# phyp Returns probability for hyperbolic DF
# qhyp Returns quantiles for hyperbolic DF
# rhyp Returns random variates for hyperbolic DF
# hypMode Computes the hyperbolic mode
# FUNCTION: DESCRIPTION:
# dnig Returns density for inverse Gaussian DF
# pnig Returns probability for for inverse Gaussian DF
# qnig Returns quantiles for for inverse Gaussian DF
# rnig Returns random variates for inverse Gaussian DF
# FUNCTION: DESCRIPTION:
# hypSlider Displays hyperbolic distribution function
# nigSlider Displays normal inverse Gausssian distribution function
################################################################################
test.gh =
function()
{
# gh() Distribution:
## RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
## set.seed(4711, kind = "Marsaglia-Multicarry")
set.seed(4711)
test = fBasics::distCheck("gh",
alpha = 1.3, beta = 0.3, delta = 1.7, mu = 0.2, lambda = 0.8,
n = 2000, robust = FALSE)
print(test)
checkTrue(mean(test) == 1)
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.hyp =
function()
{
# hyp() Distribution - Parameterization 1:
## RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
## set.seed(4711, kind = "Marsaglia-Multicarry")
set.seed(4711)
test = fBasics::distCheck("hyp",
alpha = 1.2, beta = 0.2, delta = 1.9, mu = 0.1, pm = "1",
n = 1000, robust = FALSE)
print(test)
checkTrue(mean(test) == 1)
# hyp() Distribution - Parameterization 2:
## RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
## set.seed(4711, kind = "Marsaglia-Multicarry")
set.seed(4711)
test = fBasics::distCheck("hyp",
alpha = 0.9, beta = -0.3, delta = 1.4, mu = -0.1, pm = "2",
n = 1000, robust = FALSE)
print(test)
checkTrue(mean(test) == 1)
# hyp() Distribution - Parameterization 3:
## RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
## set.seed(4711, kind = "Marsaglia-Multicarry")
set.seed(4711)
fBasics::distCheck("hyp",
alpha = 0.9, beta = -0.3, delta = 1.4, mu = -0.1, pm = "3",
n = 1000, robust = FALSE)
print(test)
checkTrue(mean(test) == 1)
# hyp() Distribution - Parameterization 4:
if (FALSE) {
RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
set.seed(4711, kind = "Marsaglia-Multicarry")
fBasics::distCheck("hyp",
alpha = 1.6, beta = -0.3, delta = 1.4, mu = 0.1, pm = "4",
n = 1000, robust = FALSE) # CHECK
print(test)
checkTrue(mean(test) == 1)
}
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.nig =
function()
{
# nig() Distribution:
## RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
## set.seed(4711, kind = "Marsaglia-Multicarry")
set.seed(4711)
test = fBasics::distCheck("nig",
alpha = 2.1, beta = 0.1, delta = 1.5, mu = -0.1,
n = 1000, robust = FALSE)
print(test)
checkTrue(mean(test) == 1)
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.hypSlider =
function()
{
# Arguments ?
# hypSlider()
# Try:
# hypSlider()
NA
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.nigSlider =
function()
{
# Arguments ?
# nigSlider
# Try:
# nigSlider()
NA
# Return Value:
return()
}
################################################################################
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