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

src/Numerics/Statistics/DescriptiveStatistics.cs

@@ -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;

src/UnitTests/StatisticsTests/DescriptiveStatisticsTests.cs

@@ -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
 }