Examples of org.apache.commons.math.stat.inference.OneWayAnovaImpl.anovaPValue()

Package org.apache.commons.math.stat.inference

Class org.apache.commons.math.stat.inference.OneWayAnovaImpl

Examples of org.apache.commons.math.stat.inference.OneWayAnovaImpl.anovaPValue()

org.apache.commons.math.stat.inference.OneWayAnovaImpl.anovaPValue()
{@inheritDoc}
This implementation uses the {@link org.apache.commons.math.distribution.FDistribution commons-math F Distribution implementation} to estimate the exactp-value, using the formula
```
 p = 1 - cumulativeProbability(F)
```
where F is the F value and cumulativeProbability is the commons-math implementation of the F distribution.


    try {
      double fValue = anova.anovaFValue(bins);
      assertEquals("2.91", String.format("%2.2f", fValue));


      double pValue = anova.anovaPValue(bins);
      assertEquals("0.000002", String.format("%1.6f", pValue));


      boolean rejectNullHypothesis = anova.anovaTest(bins, 0.05);
      assertTrue(rejectNullHypothesis);
    } catch (MathException e) {

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      // 9.264705882352942
      double fValue = anova.anovaFValue(data);
      assertEquals("9.26", String.format("%1.2f", fValue));


      // 0.002398777329392865
      double pValue = anova.anovaPValue(data);
      assertEquals("0.002", String.format("%1.3f", pValue));


      // alpha value can be 0 < alpha <= 0.5
      boolean rejectNullHypothesis = anova.anovaTest(data, 0.1);
      assertTrue(rejectNullHypothesis);

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    this.error = false;


    OneWayAnova anova = new OneWayAnovaImpl();
    try {
      fValue = anova.anovaFValue(this.magnitudeBins);
      pValue = anova.anovaPValue(this.magnitudeBins);
    } catch (Exception e) {
      error = true;
      fValue = Double.NaN;
      pValue = Double.NaN;
    }

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