Package gov.nih.mipav.model.algorithms

Class DAgostinosKsquaredTest

  • public class DAgostinosKsquaredTest
extends java.lang.Object

    This code calculates the Ksquared statistic of an input array x[]. KSquared = Z1(g1)**2 + Z2(g2)**2 If the null hypothesis of normality is true, then Ksquared is approximately chiSquared distributed with 2 degrees of freedom Expected value Standard deviation 95% quantile n = 20 1.971 2.339 6.373 n = 50 2.017 2.308 6.339 n = 100 2.026 2.267 6.271 n = 250 2.012 2.174 6.129 n = 500 2.009 2.113 6.063 n = 1000 2.000 2.062 6.038 chSquared(2) 2.000 2.000 5.991 distribution

    A typical usage would be: 

     double result[] = new double[1];
 DAgostinosKsquaredTest dkt = new DAgostinosKsquaredTest(x, result);
 dkt.run();

    • Field Summary

      Fields 
      Modifier and Type Field Description
      private double[] result
      output result
      private double[] x  

    • Method Summary

      All Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      void run()  
      void selfTest()  

      • Methods inherited from class java.lang.Object

        clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

    • Field Detail

      • x

        private double[] x

      • result

        private double[] result
        output result

    • Constructor Detail

      • DAgostinosKsquaredTest

        public DAgostinosKsquaredTest()

      • DAgostinosKsquaredTest

        public DAgostinosKsquaredTest​(double[] x,
                              double[] result)
        Parameters:
        x - Input argument
        result - outputted Ksquared test value of x

    • Method Detail

      • run

        public void run()

      • selfTest

        public void selfTest()