org.apache.commons.math3.stat.inference.TestUtils Java Examples

/**
 * One sample t test
 * @param a Input data
 * @param mu Expected value in null hypothesis
 * @return t_statistic and p_value
 */
public static double[] tTest(Array a, double mu){
    double[] ad = (double[]) ArrayUtil.copyToNDJavaArray_Double(a);
    double s = TestUtils.t(mu, ad);
    double p = TestUtils.tTest(mu, ad);
    
    return new double[]{s, p};
}
 

/**
 * unpaired, two-sided, two-sample t-test.
 * 
 * @param a Sample a.
 * @param b Sample b.
 * @return t_statistic and p_value
 */
public static double[] tTest(Array a, Array b) {
    double[] ad = (double[]) ArrayUtil.copyToNDJavaArray_Double(a);
    double[] bd = (double[]) ArrayUtil.copyToNDJavaArray_Double(b);
    double s = TestUtils.t(ad, bd);
    double p = TestUtils.tTest(ad, bd);
    
    return new double[]{s, p};
}
 

/**
 * Chi-square test
 * 
 * @param e Expected.
 * @param o Observed.
 * @return Chi-square_statistic and p_value
 */
public static double[] chiSquareTest(Array e, Array o) {
    double[] ed = (double[]) ArrayUtil.copyToNDJavaArray_Double(e);
    long[] od = (long[]) ArrayUtil.copyToNDJavaArray_Long(o);
    double s = TestUtils.chiSquare(ed, od);
    double p = TestUtils.chiSquareTest(ed, od);
    
    return new double[]{s, p};
}
 

/**
 * Chi-square test of independence
 * 
 * @param o Observed.
 * @return Chi-square_statistic and p_value
 */
public static double[] chiSquareTest(Array o) {
    long[][] od = (long[][]) ArrayUtil.copyToNDJavaArray_Long(o);
    double s = TestUtils.chiSquare(od);
    double p = TestUtils.chiSquareTest(od);
    
    return new double[]{s, p};
}
 

public void calculateAnova(double[] calorie, double[] fat, double[] carb, double[] control){
	List<double[]> classes = new ArrayList<double[]>();
	classes.add(calorie);
	classes.add(fat);
	classes.add(carb);
	classes.add(control);

	System.out.println(TestUtils.oneWayAnovaFValue(classes)); // F-value
	System.out.println(TestUtils.oneWayAnovaPValue(classes));     // P-value
	System.out.println(TestUtils.oneWayAnovaTest(classes, 0.05)); 
}
 

public PValue getPValue(Set<OWLClass> candidates, IRI referenceEntity) throws OwlSimVarianceEntityReferenceNotFoundException {
	if (!refBasedStats.getReferenceStats().containsKey(referenceEntity)) {
		throw new OwlSimVarianceEntityReferenceNotFoundException(referenceEntity);
	}

	// Create IC list for candidates provided
	double[] icData = refBasedStats.retrieveCandidatesIC(candidates);
	List<double[]> sets = new ArrayList<double[]>();
	sets.add(icData);
	sets.add(refBasedStats.getReferenceStats().get(referenceEntity).getValues());

	return new PValue(TestUtils.tTest(refBasedStats.getReferenceStats().get(referenceEntity).getMean(), icData),
			TestUtils.oneWayAnovaPValue(sets), 
			TestUtils.kolmogorovSmirnovStatistic(icData, refBasedStats.getReferenceStats().get(referenceEntity).getValues()));
}
 

public void calculateKs(double[] x, double[] y){
	double d = TestUtils.kolmogorovSmirnovStatistic(x, y);
	System.out.println(TestUtils.kolmogorovSmirnovTest(x, y, false));
	System.out.println(TestUtils.exactP(d, x.length, y.length, false));
}
 

public void getChiSquare(long[] observed, double[] expected){
	System.out.println(TestUtils.chiSquare(expected, observed));//t statistics
	System.out.println(TestUtils.chiSquareTest(expected, observed));//p value
	System.out.println(TestUtils.chiSquareTest(expected, observed, 0.05));
}
 

public void getTtest(double[] sample1, double[] sample2){
	System.out.println(TestUtils.pairedT(sample1, sample2));//t statistics
	System.out.println(TestUtils.pairedTTest(sample1, sample2));//p value
	System.out.println(TestUtils.pairedTTest(sample1, sample2, 0.05));
}
 

private static boolean isDifferent(SdkBenchmarkStatistics current, SdkBenchmarkStatistics other, double confidence) {
    return TestUtils.tTest(current, other, 1 - confidence);
}
 

private static double getonesidedPValue(double mu,double[] sample1){
	double PValue = TestUtils.tTest(mu, sample1);
	
	return PValue;
}
 

private static double getonesidedPValue(double mu,double[] sample1){
	double PValue = TestUtils.tTest(mu, sample1);
	
	return PValue;
}
 

/**
 * Paired test evaluating the null hypothesis that the mean difference 
 * between corresponding (paired) elements of the double[] arrays sample1 
 * and sample2 is zero.
 * 
 * @param a Sample a.
 * @param b Sample b.
 * @return t_statistic and p_value
 */
public static double[] pairedTTest(Array a, Array b) {
    double[] ad = (double[]) ArrayUtil.copyToNDJavaArray_Double(a);
    double[] bd = (double[]) ArrayUtil.copyToNDJavaArray_Double(b);
    double s = TestUtils.pairedT(ad, bd);
    double p = TestUtils.pairedTTest(ad, bd);
    
    return new double[]{s, p};
}
 

private static double gettwosidedPValue(double[] sample1,double[] sample2){
	
	double PValue = TestUtils.tTest(sample1, sample2);
	return PValue;
	

}
 

private static double gettwosidedPValue(double[] sample1,double[] sample2){
	
	double PValue = TestUtils.tTest(sample1, sample2);
	return PValue;
	

}