Commons Math example source code file (TTestCases)

This example Commons Math source code file (TTestCases) is included in the DevDaily.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" ^TM.

Java - Commons Math tags/keywords

apache, failed, false, false, license, license, one-sample, r, r, see, true, ttest, ttest, you

The Commons Math TTestCases source code

# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
#------------------------------------------------------------------------------
# R source file to validate TTest tests in
# org.apache.commons.math.inference.TTestImpl
#
# To run the test, install R, put this file and testFunctions
# into the same directory, launch R from this directory and then enter
# source("<name-of-this-file>")
#
# R functions used
# t.test(x, y = NULL, alternative = c("two.sided", "less", "greater"),
# mu = 0, paired = FALSE, var.equal = FALSE, ... )
# Arguments
#   x  a numeric vector of data values.
#   y  an optional numeric vector data values.
#   alternative 	a character string specifying the alternative hypothesis, 
#     must be one of "two.sided" (default), "greater" or "less". You can specify
#     just the initial letter.
#   mu  a number indicating the true value of the mean (or difference in means
#      if you are performing a two sample test).
#   paired 	a logical indicating whether you want a paired t-test.
#   var.equal 	a logical variable indicating whether to treat the two
#     variances as being equal. 
#     If TRUE then the pooled variance is used to estimate the variance,
#     otherwise the Welch (or Satterthwaite) approximation to the degrees
#     of freedom is used.
#------------------------------------------------------------------------------
tol <- 1E-10                       # error tolerance for tests
#------------------------------------------------------------------------------
# Function definitions
#------------------------------------------------------------------------------
source("testFunctions")           # utility test functions
#------------------------------------------------------------------------------
# Verification function
#
verifyTest <- function(out,expectedP, expectedT,
  tol) {
  if (assertEquals(expectedP, out$p.value, tol,
     "Ttest p value")) {
     displayPadded(output, SUCCEEDED, 80)
  } else {
     displayPadded(output, FAILED, 80)
  }  
  output <- c("t test test statistic") 
  if (assertEquals(expectedT, out$statistic, tol,
      "Ttest t statistic")) {
      displayPadded(output, SUCCEEDED, 80)
  } else {
      displayPadded(output, FAILED, 80)
  }          
  displayDashes(WIDTH)
}

cat("One-sample, two-sided TTest test cases \n")
sample1 <- c(93.0, 103.0, 95.0, 101.0, 91.0, 105.0, 96.0, 94.0, 101.0,  88.0,
                      98.0, 94.0, 101.0, 92.0, 95.0)
out <- t.test(sample1, mu=100.0)
expectedP <-  0.0136390585873
expectedT<- -2.81976445346
verifyTest(out,expectedP, expectedT, tol) 

cat("One-sample, one-sided TTest test cases \n")
sample1 <- c(2, 0, 6, 6, 3, 3, 2, 3, -6, 6, 6, 6, 3, 0, 1, 1, 0, 2, 3, 3)
out <- t.test(sample1, mu=0.0, alternative="g")
expectedP <-  0.000521637019637
expectedT<- 3.86485535541
verifyTest(out,expectedP, expectedT, tol) 

cat("Homoscedastic TTest test cases \n")
sample1 <- c(2, 4, 6, 8, 10, 97)
sample2 <- c(4, 6, 8, 10, 16)
out <- t.test(sample1,sample2,var.equal = TRUE)
expectedP <-  0.4833963785
expectedT<- 0.73096310086
verifyTest(out,expectedP, expectedT, tol)
 
cat("Heteroscedastic TTest test cases \n")
sample1 <- c(7, -4, 18, 17, -3, -5, 1, 10, 11, -2)
sample2 <- c(-1, 12, -1, -3, 3, -5, 5, 2, -11, -1, -3) 
out <- t.test(sample1,sample2,var.equal = FALSE)
expectedP <-  0.128839369622
expectedT<- 1.60371728768
verifyTest(out,expectedP, expectedT, tol)

cat("Small sample, heteroscedastic test cases \n")
sample1 <- c(1,3)
sample2 <- c(4,5)
out <- t.test(sample1,sample2,var.equal = FALSE)
expectedP <-  0.198727388935
expectedT<- -2.2360679775
verifyTest(out,expectedP, expectedT, tol)