public void MovingP2QuantileEstimatorMedianTest1(int n, int windowSize, double probability, double relativeThreshold,
double minSuccessRate)
{
var random = new Random();
double[] data = new double[n];
for (int i = 0; i < n; i++)
{
data[i] = 10 + Math.Sin(i / 20.0) * 5 + random.NextDouble(-3, 3);
if (random.Next(10) == 0 && i > windowSize / 2)
{
data[i] += random.Next(20, 50);
}
data[i] = Math.Round(data[i], 3);
}
var mp2Estimator = new MovingP2QuantileEstimator(probability, windowSize);
var phEstimator = new PartitioningHeapsMovingQuantileEstimator(windowSize, probability);
var outputBuilder = new StringBuilder();
outputBuilder.AppendLine("i,data,estimation,true");
int successCounter = 0;
for (int i = 0; i < n; i++)
{
mp2Estimator.Add(data[i]);
phEstimator.Add(data[i]);
double mp2Estimation = mp2Estimator.GetQuantile();
double trueValue = phEstimator.GetQuantile();
if (Math.Abs(mp2Estimation - trueValue) / trueValue < relativeThreshold)
{
successCounter++;
}
outputBuilder.Append(i);
outputBuilder.Append(',');
outputBuilder.Append(data[i].ToString(TestCultureInfo.Instance));
outputBuilder.Append(',');
outputBuilder.Append(mp2Estimation.ToString(TestCultureInfo.Instance));
outputBuilder.Append(',');
outputBuilder.Append(trueValue.ToString(TestCultureInfo.Instance));
outputBuilder.AppendLine();
}
double actualSuccessRate = successCounter * 1.0 / n;
output.WriteLine("ExpectedSuccessRate = " + minSuccessRate.ToString(TestCultureInfo.Instance));
output.WriteLine("ActualSuccessRate = " + actualSuccessRate.ToString(TestCultureInfo.Instance));
output.WriteLine();
output.WriteLine(outputBuilder.ToString());
Assert.True(successCounter * 1.0 / n > minSuccessRate);
}
public void HyndmanFanPartitioningHeapsQuantileEstimatorTest()
{
double[] fullSource = { 1, 3, 6, 10, 15, 21, 28, 36, 45, 55, 66 };
var probabilities = Enumerable.Range(0, 101).Select(x => (Probability)(x / 100.0)).ToArray();
var types = new[]
{
HyndmanFanType.Type1, HyndmanFanType.Type2, HyndmanFanType.Type3, HyndmanFanType.Type4, HyndmanFanType.Type5,
HyndmanFanType.Type6, HyndmanFanType.Type7, HyndmanFanType.Type8, HyndmanFanType.Type9,
};
var comparer = new AbsoluteEqualityComparer(1e-2);
var shuffler = new Shuffler(new Random(42));
for (int n = 1; n <= fullSource.Length; n++)
{
double[] source = fullSource.Take(n).ToArray();
var sample = new Sample(source);
foreach (var type in types)
{
for (int i = 0; i < probabilities.Length; i++)
{
var probability = probabilities[i];
var hyEstimator = new HyndmanFanQuantileEstimator(type);
double expectedValue = hyEstimator.GetQuantile(sample, probability);
var phEstimator = new PartitioningHeapsMovingQuantileEstimator(n, probability, type);
shuffler.Shuffle(source);
foreach (double value in source)
{
phEstimator.Add(value);
}
double actualValue = phEstimator.GetQuantile();
if (!comparer.Equals(expectedValue, actualValue))
{
Output.WriteLine($"n = {n}, type = {type}, p = {probability}: E = {expectedValue}, A = {actualValue}");
}
Assert.Equal(expectedValue, actualValue, comparer);
}
}
}
}
