public static double Calculate([NotNull] double[] values)
{
try
{
var clearedValues = TukeyOutlierDetector.Create(values).WithoutAllOutliers(values).ToList();
int n = clearedValues.Count;
var quartiles = Quartiles.Create(clearedValues);
var moments = Moments.Create(clearedValues);
double mValue = 0;
double binSize = AdaptiveHistogramBuilder.GetOptimalBinSize(n, moments.StandardDeviation);
if (Abs(binSize) < 1e-9)
{
binSize = 1;
}
while (true)
{
var histogram = HistogramBuilder.Adaptive.Build(clearedValues, 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 > quartiles.Max - quartiles.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)
}
}
public void Run()
{
var simple = SimpleQuantileEstimator.Instance;
var hd = HarrellDavisQuantileEstimator.Instance;
var detectors = new[]
{
new Detector("TukeySimple", values => TukeyOutlierDetector.Create(values, quantileEstimator: simple)),
new Detector("TukeyHd", values => TukeyOutlierDetector.Create(values, quantileEstimator: hd)),
new Detector("MadSimple", values => MadOutlierDetector.Create(values, quantileEstimator: simple)),
new Detector("MadHd", values => MadOutlierDetector.Create(values, quantileEstimator: hd)),
new Detector("DoubleMadSimple", values => DoubleMadOutlierDetector.Create(values, quantileEstimator: simple)),
new Detector("DoubleMadHd", values => DoubleMadOutlierDetector.Create(values, quantileEstimator: hd))
};
Case.DumpBaseSample();
BuildTable(detectors, new[] { new Case(1, 0), new Case(2, 0), new Case(3, 0) });
BuildTable(detectors, new[] { new Case(0, 1), new Case(0, 2), new Case(0, 3) });
BuildTable(detectors, new[] { new Case(1, 1), new Case(2, 2), new Case(3, 3) });
}
public Statistics(IEnumerable <double> values)
{
OriginalValues = values.Where(d => !double.IsNaN(d)).ToArray();
SortedValues = OriginalValues.OrderBy(value => value).ToArray();
N = SortedValues.Count;
if (N == 0)
{
throw new InvalidOperationException("Sequence of values contains no elements, Statistics can't be calculated");
}
var quartiles = Quartiles.FromSorted(SortedValues);
Min = quartiles.Min;
Q1 = quartiles.Q1;
Median = quartiles.Median;
Q3 = quartiles.Q3;
Max = quartiles.Max;
InterquartileRange = quartiles.InterquartileRange;
var moments = Moments.Create(SortedValues);
Mean = moments.Mean;
StandardDeviation = moments.StandardDeviation;
Variance = moments.Variance;
Skewness = moments.Skewness;
Kurtosis = moments.Kurtosis;
var tukey = TukeyOutlierDetector.FromQuartiles(quartiles);
LowerFence = tukey.LowerFence;
UpperFence = tukey.UpperFence;
AllOutliers = SortedValues.Where(tukey.IsOutlier).ToArray();
LowerOutliers = SortedValues.Where(tukey.IsLowerOutlier).ToArray();
UpperOutliers = SortedValues.Where(tukey.IsUpperOutlier).ToArray();
outlierDetector = tukey;
StandardError = StandardDeviation / Math.Sqrt(N);
ConfidenceInterval = new ConfidenceInterval(Mean, StandardError, N);
Percentiles = new PercentileValues(SortedValues);
}
public Statistics(IEnumerable <double> values)
{
var sortedValues = new SegmentedList <double>(values.Where(d => !double.IsNaN(d)));
sortedValues.Sort();
if (sortedValues.Count < 1)
{
return;
}
var quartiles = Quartiles.FromSorted(sortedValues);
Min = quartiles.Min;
Q1 = quartiles.Q1;
Median = quartiles.Median;
Q3 = quartiles.Q3;
Max = quartiles.Max;
Mean = sortedValues.Average();
var tukey = TukeyOutlierDetector.FromQuartiles(quartiles);
LowerFence = tukey.LowerFence;
UpperFence = tukey.UpperFence;
P0 = SimpleQuantileEstimator.Instance.GetQuantileFromSorted(sortedValues, 0.0);
P25 = SimpleQuantileEstimator.Instance.GetQuantileFromSorted(sortedValues, 0.25);
P50 = SimpleQuantileEstimator.Instance.GetQuantileFromSorted(sortedValues, 0.50);
P67 = SimpleQuantileEstimator.Instance.GetQuantileFromSorted(sortedValues, 0.67);
P80 = SimpleQuantileEstimator.Instance.GetQuantileFromSorted(sortedValues, 0.80);
P85 = SimpleQuantileEstimator.Instance.GetQuantileFromSorted(sortedValues, 0.85);
P90 = SimpleQuantileEstimator.Instance.GetQuantileFromSorted(sortedValues, 0.90);
P95 = SimpleQuantileEstimator.Instance.GetQuantileFromSorted(sortedValues, 0.95);
P99 = SimpleQuantileEstimator.Instance.GetQuantileFromSorted(sortedValues, 0.99);
P100 = SimpleQuantileEstimator.Instance.GetQuantileFromSorted(sortedValues, 1.00);
}
public void TukeyOutlierDetectorHdQeTest([NotNull] string testDataKey) => Check(HdQeTestDataMap[testDataKey],
values => TukeyOutlierDetector.Create(values, quantileEstimator: HarrellDavisQuantileEstimator.Instance));
public void TukeyOutlierDetectorSimpleQeTest([NotNull] string testDataKey) => Check(SimpleQeTestDataMap[testDataKey],
values => TukeyOutlierDetector.Create(values, quantileEstimator: SimpleQuantileEstimator.Instance));
