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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 - 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
################################################################################
# FUNCTION: SKEW NORMAL DISTRIBUTION:
# dsnorm Density for the skew normal Distribution
# psnorm Probability function for the skew NORM
# qsnorm Quantile function for the skew NORM
# rsnorm Random Number Generator for the skew NORM
# FUNCTION: PARAMETER ESTIMATION:
# snormFit Fit the parameters for a skew Normal distribution
# FUNCTION: SLIDER:
# snormSlider Displays Normal Distribution and RVS
################################################################################
test.snormDist <-
function()
{
# Normal Distribution:
RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
set.seed(4711, kind = "Marsaglia-Multicarry")
# Test:
test = fBasics::distCheck("norm", mean = 0, sd = 1, robust = FALSE)
print(test)
checkTrue(sum(test) == 3)
# Skew Normal Distribution:
RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
set.seed(4711, kind = "Marsaglia-Multicarry")
# Test:
test = fBasics::distCheck("snorm", mean = 0, sd = 1, xi = 1.5, robust = FALSE)
print(test)
checkTrue(sum(test) == 3)
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.snormFit <-
function()
{
# Parameter Estimation:
# snormFit - Fit the parameters for a skew Normal distribution
# Skew Normal Distribution:
RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
set.seed(4711, kind = "Marsaglia-Multicarry")
# Series:
x = rsnorm(n = 1000, mean = 0, sd = 1, xi = 1.5)
# Fit:
fit = snormFit(x)
print(fit)
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.snormSlider <-
function()
{
# Try Distribution:
# snormSlider(type = "dist")
NA
# Try Random Variates:
RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
set.seed(4711, kind = "Marsaglia-Multicarry")
# snormSlider(type = "rand")
NA
# Return Value:
return()
}
################################################################################
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