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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: DISTRIBUTIONAL TESTS:
# ks2Test Performs a two sample Kolmogorov-Smirnov test
# FUNCTION: LOCATION TESTS:
# locationTest Performs locations tests on two samples
# .tTest Unpaired t test for differences in mean
# .kw2Test Kruskal-Wallis test for differences in locations
# FUNCTION: VARIANCE TESTS:
# varianceTest Performs variance tests on two samples
# .varfTest F test for differences in variances
# .bartlett2Test Bartlett's test for differences in variances
# .fligner2Test Fligner-Killeen test for differences in variances
# FUNCTION: SCALE TESTS:
# scaleTest Performs scale tests on two samples
# .ansariTest Ansari-Bradley test for differences in scale
# .moodTest Mood test for differences in scale
# dansariw Returns density of the Ansari W statistic
# pansariw Returns probabilities of the Ansari W statistic
# qansariw Returns quantiles of the Ansari W statistic
# FUNCTION: CORRELATION TESTS:
# correlationTest Performs correlation tests on two samples
# pearsonTest Pearson product moment correlation coefficient
# kendallTest Kendall's tau correlation test
# spearmanTest Spearman's rho correlation test
################################################################################
test.distributionTest =
function()
{
# Data:
## RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
## set.seed(4711, kind = "Marsaglia-Multicarry")
set.seed(4711)
X = rnorm(100)
Y = rt(50, df = 3)
# Two Sample Kolmogorov-Smirnov Test:
TEST = ks2Test(X, Y)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.locationTests =
function()
{
# Data:
## RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
## set.seed(4711, kind = "Marsaglia-Multicarry")
set.seed(4711)
X = rnorm(100)
Y = rt(50, df = 3)
# Location t-Test:
TEST = fBasics:::.tTest(X, Y)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
# Location kw2-Test:
TEST = fBasics:::.kw2Test(X, Y)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.varianceTests =
function()
{
# Data:
## RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
## set.seed(4711, kind = "Marsaglia-Multicarry")
set.seed(4711)
X = rnorm(100)
Y = rt(50, df = 3)
# Variance F-Test:
TEST = fBasics:::.varfTest(X, Y)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
# Variance Bartlett-Test:
TEST = fBasics:::.bartlett2Test(X, Y)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
# Variance Fligner-Test:
TEST = fBasics:::.fligner2Test(X, Y)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.scaleTests =
function()
{
# Data:
## RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
## set.seed(4711, kind = "Marsaglia-Multicarry")
set.seed(4711)
X = rnorm(100)
Y = rt(50, df = 3)
# Scale Ansari-Test:
TEST = fBasics:::.ansariTest(X, Y)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
# Scale Mood-Test:
TEST = fBasics:::.moodTest(X, Y)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
# Return Value:
return()
}
# ------------------------------------------------------------------------------
test.correlationTests =
function()
{
# Data:
## RNGkind(kind = "Marsaglia-Multicarry", normal.kind = "Inversion")
## set.seed(4711, kind = "Marsaglia-Multicarry")
set.seed(4711)
X = rnorm(100)
Y = rt(100, df = 3)
# Correlation Pearson-Test:
TEST = pearsonTest(X, Y)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
# Correlation Kendall-Test:
TEST = kendallTest(X, Y)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
# Correlation Spearman-Test:
TEST = spearmanTest(X, Y)
print(TEST)
checkIdentical(as.character(class(TEST)), "fHTEST")
# Return Value:
return()
}
################################################################################
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