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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: VARIANCE-1 STUDENT-T DISTRIBUTION:
# dstd Density for the Student-t Distribution
# pstd Probability function for the Student-t Distribution
# qstd Quantile function for the Student-t Distribution
# rstd Random Number Generator for the Student-t
# FUNCTION: SKEW VARIANCE-1 STUDENT-T DISTRIBUTION:
# dsstd Density for the skewed Student-t Distribution
# psstd Probability function for the skewed STD
# qsstd Quantile function for the skewed STD
# rsstd Random Number Generator for the skewed STD
# stdSlider Displays Variance-1 Student-t Distribution and RVS
# FUNCTION: PARAMETER ESTIMATION:
# stdFit Fit the parameters for a Sudent-t distribution
# sstdFit Fit the parameters for a skew Sudent-t distribution
################################################################################
test.sstdDist <-
function()
{
# Standardized Student-t Distribution:
RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
set.seed(4711, kind = "Marsaglia-Multicarry")
# Test:
test = fBasics::distCheck("std", mean = 0, sd = 1, nu = 5, robust = FALSE)
print(test)
# Skew Standardized Student-t Distribution:
RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
set.seed(4711, kind = "Marsaglia-Multicarry")
# Test:
test = fBasics::distCheck("sstd", mean = 0, sd = 1, nu = 5, xi = 1.5, robust = FALSE)
print(test)
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.stdFit <-
function()
{
# Fit the parameters for a Student-t distribution
# stdFit - Fit the parameters for a Sudent-t distribution
# Standardized Student-t Distribution:
RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
set.seed(4711, kind = "Marsaglia-Multicarry")
# Series:
x = rstd(n = 2500, mean = 0, sd = 1, nu = 5)
# Fit:
fit = stdFit(x)
print(fit)
# Fit the parameters for a skew Sudent-t distribution
# sstdFit - Fit the parameters for a Sudent-t distribution
# Skew Standardized Student-t Distribution:
RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
set.seed(4711, kind = "Marsaglia-Multicarry")
# Series:
x = rsstd(n = 2500, mean = 0, sd = 1, nu = 5, xi = 1.5)
# Fit:
fit = sstdFit(x)
print(fit)
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.sstdSlider <-
function()
{
# Try Distribution:
# sstdSlider(type = "dist")
NA
# Try Random Variates:
RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
set.seed(4711, kind = "Marsaglia-Multicarry")
# sstdSlider(type = "rand")
NA
# Return Value:
return()
}
################################################################################
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