public static double CalculateMValue([NotNull] Statistics originalStatistics)
{
try
{
var s = new Statistics(originalStatistics.WithoutOutliers());
double mValue = 0;
double binSize = s.GetOptimalBinSize();
if (Abs(binSize) < 1e-9)
{
binSize = 1;
}
while (true)
{
var histogram = HistogramBuilder.Adaptive.BuildWithFixedBinSize(s.GetValues(), binSize);
var x = new List <int> {
0
};
x.AddRange(histogram.Bins.Select(bin => bin.Count));
x.Add(0);
int sum = 0;
for (int i = 1; i < x.Count; i++)
{
sum += Abs(x[i] - x[i - 1]);
}
mValue = Max(mValue, sum * 1.0 / x.Max());
if (binSize > s.Max - s.Min)
{
break;
}
binSize *= 2.0;
}
return(mValue);
}
catch (Exception)
{
return(1); // In case of any bugs, we return 1 because it's an invalid value (mvalue is always >= 2)
}
}
private static bool AreSame(Statistics x, Statistics y)
{
if (x.N >= 3 && y.N >= 3)
{
var tost = StatisticalTestHelper.CalculateTost(MannWhitneyTest.Instance, x.GetValues().ToArray(), y.GetValues().ToArray(), RelativeThreshold.Default);
if (tost.Conclusion != EquivalenceTestConclusion.Unknown)
{
return(tost.Conclusion == EquivalenceTestConclusion.Same);
}
}
return(Math.Abs(x.Mean - y.Mean) < Math.Abs(x.Mean + y.Mean) / 2 * 0.01);
}
