# 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")
    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")
    X = rnorm(100)
    Y = rt(50, df = 3)    
 
    # Location t-Test:
    TEST = .tTest(X, Y)
    print(TEST)
    checkIdentical(as.character(class(TEST)), "fHTEST")
    
    # Location kw2-Test:
    TEST = .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")
    X = rnorm(100)
    Y = rt(50, df = 3)              
        
    # Variance F-Test:
    TEST = .varfTest(X, Y)
    print(TEST)
    checkIdentical(as.character(class(TEST)), "fHTEST")
    
    # Variance Bartlett-Test:
    TEST = .bartlett2Test(X, Y)
    print(TEST)
    checkIdentical(as.character(class(TEST)), "fHTEST")
    
    # Variance Fligner-Test:
    TEST = .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")
    X = rnorm(100)
    Y = rt(50, df = 3)           
        
    # Scale Ansari-Test:
    TEST = .ansariTest(X, Y)
    print(TEST)
    checkIdentical(as.character(class(TEST)), "fHTEST")
    
    # Scale Mood-Test:
    TEST = .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")
    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()
}

    
################################################################################