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Statistics: descriptive statistics which are not available must be NaN #210

pull/222/head
Christoph Ruegg 12 years ago
parent
4b7d61e920
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3e1cd36698
2 changed files with 49 additions and 16 deletions
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  1. 21
      src/Numerics/Statistics/DescriptiveStatistics.cs
  2. 44
      src/UnitTests/StatisticsTests/DescriptiveStatisticsTests.cs

21
src/Numerics/Statistics/DescriptiveStatistics.cs
View File

@ -36,13 +36,13 @@ namespace MathNet.Numerics.Statistics
/// <summary>
/// Computes the basic statistics of data set. The class meets the
/// NIST standard of accuracy for mean, variance, and standard deviation
/// (the only statistics they provide exact values for) and exceeds them
/// (the only statistics they provide exact values for) and exceeds them
/// in increased accuracy mode.
/// </summary>
public class DescriptiveStatistics
{
/// <summary>
/// Initializes a new instance of the <see cref="DescriptiveStatistics"/> class.
/// Initializes a new instance of the <see cref="DescriptiveStatistics"/> class.
/// </summary>
/// <param name="data">The sample data.</param>
/// <param name="increasedAccuracy">
@ -71,7 +71,7 @@ namespace MathNet.Numerics.Statistics
}
/// <summary>
/// Initializes a new instance of the <see cref="DescriptiveStatistics"/> class.
/// Initializes a new instance of the <see cref="DescriptiveStatistics"/> class.
/// </summary>
/// <param name="data">The sample data.</param>
/// <param name="increasedAccuracy">
@ -189,8 +189,6 @@ namespace MathNet.Numerics.Statistics
SetStatistics(mean, variance, skewness, kurtosis, minimum, maximum, n);
}
/// <summary>
/// Computes descriptive statistics from a stream of nullable data values.
/// </summary>
@ -230,9 +228,7 @@ namespace MathNet.Numerics.Statistics
}
}
}
SetStatistics(mean, variance, skewness, kurtosis, minimum, maximum, n);
}
/// <summary>
@ -272,9 +268,7 @@ namespace MathNet.Numerics.Statistics
maximum = xi;
}
}
SetStatistics((double)mean, (double)variance, (double)skewness, (double)kurtosis, (double)minimum, (double)maximum, n);
}
/// <summary>
@ -318,7 +312,6 @@ namespace MathNet.Numerics.Statistics
}
}
SetStatistics((double)mean, (double)variance, (double)skewness, (double)kurtosis, (double)minimum, (double)maximum, n);
}
/// <summary>
@ -335,6 +328,14 @@ namespace MathNet.Numerics.Statistics
{
Mean = mean;
Count = n;
Minimum = double.NaN;
Maximum = double.NaN;
Variance = double.NaN;
StandardDeviation = double.NaN;
Skewness = double.NaN;
Kurtosis = double.NaN;
if (n > 0)
{
Minimum = minimum;

44
src/UnitTests/StatisticsTests/DescriptiveStatisticsTests.cs
View File

@ -95,7 +95,7 @@ namespace MathNet.Numerics.UnitTests.StatisticsTests
[TestCase("lew", 12, -0.050606638756334, -1.49604979214447, -162, -579, 300, 200)]
[TestCase("mavro", 11, 0.64492948110824, -0.82052379677456, 2.0018, 2.0013, 2.0027, 50)]
[TestCase("michelso", 11, -0.0185388637725746, 0.33968459842539, 299.85, 299.62, 300.07, 100)]
[TestCase("numacc1", 15, 0, 0, 10000002, 10000001, 10000003, 3)]
[TestCase("numacc1", 15, 0, double.NaN, 10000002, 10000001, 10000003, 3)]
[TestCase("numacc2", 13, 0, -2.003003003003, 1.2, 1.1, 1.3, 1001)]
[TestCase("numacc3", 9, 0, -2.003003003003, 1000000.2, 1000000.1, 1000000.3, 1001)]
[TestCase("numacc4", 7, 0, -2.00300300299913, 10000000.2, 10000000.1, 10000000.3, 1001)]
@ -128,7 +128,7 @@ namespace MathNet.Numerics.UnitTests.StatisticsTests
[TestCase("lew", -0.050606638756334, -1.49604979214447, -162, -579, 300, 200)]
[TestCase("mavro", 0.64492948110824, -0.82052379677456, 2.0018, 2.0013, 2.0027, 50)]
[TestCase("michelso", -0.0185388637725746, 0.33968459842539, 299.85, 299.62, 300.07, 100)]
[TestCase("numacc1", 0, 0, 10000002, 10000001, 10000003, 3)]
[TestCase("numacc1", 0, double.NaN, 10000002, 10000001, 10000003, 3)]
[TestCase("numacc2", 0, -2.003003003003, 1.2, 1.1, 1.3, 1001)]
[TestCase("numacc3", 0, -2.003003003003, 1000000.2, 1000000.1, 1000000.3, 1001)]
[TestCase("numacc4", 0, -2.00300300299913, 10000000.2, 10000000.1, 10000000.3, 1001)]
@ -160,7 +160,7 @@ namespace MathNet.Numerics.UnitTests.StatisticsTests
[TestCase("lew", 14, -0.050606638756334, -1.49604979214447, -162, -579, 300, 200)]
[TestCase("mavro", 11, 0.64492948110824, -0.82052379677456, 2.0018, 2.0013, 2.0027, 50)]
[TestCase("michelso", 11, -0.0185388637725746, 0.33968459842539, 299.85, 299.62, 300.07, 100)]
[TestCase("numacc1", 15, 0, 0, 10000002, 10000001, 10000003, 3)]
[TestCase("numacc1", 15, 0, double.NaN, 10000002, 10000001, 10000003, 3)]
[TestCase("numacc2", 13, 0, -2.003003003003, 1.2, 1.1, 1.3, 1001)]
[TestCase("numacc3", 9, 0, -2.003003003003, 1000000.2, 1000000.1, 1000000.3, 1001)]
[TestCase("numacc4", 7, 0, -2.00300300299913, 10000000.2, 10000000.1, 10000000.3, 1001)]
@ -192,7 +192,7 @@ namespace MathNet.Numerics.UnitTests.StatisticsTests
[TestCase("lew", 14, -0.050606638756334, -1.49604979214447, -162, -579, 300, 200)]
[TestCase("mavro", 11, 0.64492948110824, -0.82052379677456, 2.0018, 2.0013, 2.0027, 50)]
[TestCase("michelso", 11, -0.0185388637725746, 0.33968459842539, 299.85, 299.62, 300.07, 100)]
[TestCase("numacc1", 15, 0, 0, 10000002, 10000001, 10000003, 3)]
[TestCase("numacc1", 15, 0, double.NaN, 10000002, 10000001, 10000003, 3)]
[TestCase("numacc2", 13, 0, -2.003003003003, 1.2, 1.1, 1.3, 1001)]
[TestCase("numacc3", 9, 0, -2.003003003003, 1000000.2, 1000000.1, 1000000.3, 1001)]
[TestCase("numacc4", 7, 0, -2.00300300299913, 10000000.2, 10000000.1, 10000000.3, 1001)]
@ -223,7 +223,7 @@ namespace MathNet.Numerics.UnitTests.StatisticsTests
[TestCase("lew", -0.050606638756334, -1.49604979214447, -162, -579, 300, 200)]
[TestCase("mavro", 0.64492948110824, -0.82052379677456, 2.0018, 2.0013, 2.0027, 50)]
[TestCase("michelso", -0.0185388637725746, 0.33968459842539, 299.85, 299.62, 300.07, 100)]
[TestCase("numacc1", 0, 0, 10000002, 10000001, 10000003, 3)]
[TestCase("numacc1", 0, double.NaN, 10000002, 10000001, 10000003, 3)]
[TestCase("numacc2", 0, -2.003003003003, 1.2, 1.1, 1.3, 1001)]
[TestCase("numacc3", 0, -2.003003003003, 1000000.2, 1000000.1, 1000000.3, 1001)]
[TestCase("numacc4", 0, -2.00300300299913, 10000000.2, 10000000.1, 10000000.3, 1001)]
@ -255,7 +255,7 @@ namespace MathNet.Numerics.UnitTests.StatisticsTests
[TestCase("lew", 14, -0.050606638756334, -1.49604979214447, -162, -579, 300, 200)]
[TestCase("mavro", 11, 0.64492948110824, -0.82052379677456, 2.0018, 2.0013, 2.0027, 50)]
[TestCase("michelso", 11, -0.0185388637725746, 0.33968459842539, 299.85, 299.62, 300.07, 100)]
[TestCase("numacc1", 15, 0, 0, 10000002, 10000001, 10000003, 3)]
[TestCase("numacc1", 15, 0, double.NaN, 10000002, 10000001, 10000003, 3)]
[TestCase("numacc2", 13, 0, -2.003003003003, 1.2, 1.1, 1.3, 1001)]
[TestCase("numacc3", 9, 0, -2.003003003003, 1000000.2, 1000000.1, 1000000.3, 1001)]
[TestCase("numacc4", 7, 0, -2.00300300299913, 10000000.2, 10000000.1, 10000000.3, 1001)]
@ -271,6 +271,38 @@ namespace MathNet.Numerics.UnitTests.StatisticsTests
Assert.AreEqual(stats.Maximum, max);
Assert.AreEqual(stats.Count, count);
}
[Test]
public void ShortSequences()
{
var stats0 = new DescriptiveStatistics(new double[0]);
Assert.That(stats0.Skewness, Is.NaN);
Assert.That(stats0.Kurtosis, Is.NaN);
var stats1 = new DescriptiveStatistics(new[] { 1.0 });
Assert.That(stats1.Skewness, Is.NaN);
Assert.That(stats1.Kurtosis, Is.NaN);
var stats2 = new DescriptiveStatistics(new[] { 1.0, 2.0 });
Assert.That(stats2.Skewness, Is.NaN);
Assert.That(stats2.Kurtosis, Is.NaN);
var stats3 = new DescriptiveStatistics(new[] { 1.0, 2.0, -3.0 });
Assert.That(stats3.Skewness, Is.Not.NaN);
Assert.That(stats3.Kurtosis, Is.NaN);
var stats4 = new DescriptiveStatistics(new[] { 1.0, 2.0, -3.0, -4.0 });
Assert.That(stats4.Skewness, Is.Not.NaN);
Assert.That(stats4.Kurtosis, Is.Not.NaN);
}
[Test]
public void ZeroVarianceSequence()
{
var stats = new DescriptiveStatistics(new[] { 2.0, 2.0, 2.0, 2.0 });
Assert.That(stats.Skewness, Is.NaN);
Assert.That(stats.Kurtosis, Is.NaN);
}
}
#endif
}

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