diff --git a/src/Numerics/ExcelFunctions.cs b/src/Numerics/ExcelFunctions.cs
index 53763368..6904b6e0 100644
--- a/src/Numerics/ExcelFunctions.cs
+++ b/src/Numerics/ExcelFunctions.cs
@@ -33,6 +33,7 @@ using MathNet.Numerics.Distributions;
 using MathNet.Numerics.Statistics;
 
 // ReSharper disable InconsistentNaming
+
 namespace MathNet.Numerics
 {
     /// <summary>
@@ -85,6 +86,12 @@ namespace MathNet.Numerics
                     throw new ArgumentOutOfRangeException("quant");
             }
         }
+
+        public static double PERCENTRANK(double[] array, double x)
+        {
+            return array.QuantileRank(x, RankDefinition.Min);
+        }
     }
 }
+
 // ReSharper restore InconsistentNaming
diff --git a/src/Numerics/Statistics/RankDefinition.cs b/src/Numerics/Statistics/RankDefinition.cs
index a34e3825..063a24cd 100644
--- a/src/Numerics/Statistics/RankDefinition.cs
+++ b/src/Numerics/Statistics/RankDefinition.cs
@@ -44,6 +44,8 @@ namespace MathNet.Numerics.Statistics
         Max = 3,
 
         /// <summary>Permutation with increasing values at each index of ties.</summary>
-        First = 4
+        First = 4,
+
+        EmpiricalCDF = 5
     }
-}
+}
\ No newline at end of file
diff --git a/src/Numerics/Statistics/SortedArrayStatistics.cs b/src/Numerics/Statistics/SortedArrayStatistics.cs
index 95397227..f00e1244 100644
--- a/src/Numerics/Statistics/SortedArrayStatistics.cs
+++ b/src/Numerics/Statistics/SortedArrayStatistics.cs
@@ -282,6 +282,89 @@ namespace MathNet.Numerics.Statistics
             }
         }
 
+        /// <summary>
+        /// Estimates the empirical cummulative distribution function (CDF) at x from the sorted data array (ascending).
+        /// </summary>
+        /// <param name="data">The data sample sequence.</param>
+        /// <param name="x">The value where to estimate the CDF at.</param>
+        public static double EmpiricalCDF(double[] data, double x)
+        {
+            if (x < data[0]) return 0.0;
+            if (x >= data[data.Length - 1]) return 1.0;
+
+            int right = Array.BinarySearch(data, x);
+            if (right >= 0)
+            {
+                while (right < data.Length - 1 && data[right + 1] == data[right])
+                {
+                    right++;
+                }
+                return (right + 1)/(double)(data.Length);
+            }
+
+            return (~right)/(double)(data.Length);
+        }
+
+        /// <summary>
+        /// Estimates the quantile tau from the sorted data array (ascending).
+        /// The tau-th quantile is the data value where the cumulative distribution
+        /// function crosses tau. The quantile definition can be specificed to be compatible
+        /// with an existing system.
+        /// </summary>
+        /// <param name="data">The data sample sequence.</param>
+        /// <param name="x">Quantile value.</param>
+        /// <param name="definition">Rank definition, to choose how ties should be handled and what product/definition it should be consistent with</param>
+        public static double QuantileRank(double[] data, double x, RankDefinition definition = RankDefinition.Default)
+        {
+            if (x < data[0]) return 0.0;
+            if (x >= data[data.Length - 1]) return 1.0;
+
+            int right = Array.BinarySearch(data, x);
+            if (right >= 0)
+            {
+                int left = right;
+                while (left > 0 && data[left - 1] == data[left])
+                {
+                    left--;
+                }
+                while (right < data.Length - 1 && data[right + 1] == data[right])
+                {
+                    right++;
+                }
+
+                switch (definition)
+                {
+                    case RankDefinition.EmpiricalCDF:
+                        return (right + 1)/(double)(data.Length);
+                    case RankDefinition.Max:
+                        return right/(double)(data.Length - 1);
+                    case RankDefinition.Min:
+                        return left/(double)(data.Length - 1);
+                    case RankDefinition.Average:
+                        return (left/(double)(data.Length - 1) + right/(double)(data.Length - 1))/2;
+                    default:
+                        throw new NotSupportedException();
+                }
+            }
+            else
+            {
+                right = ~right;
+                int left = right - 1;
+
+                switch (definition)
+                {
+                    case RankDefinition.EmpiricalCDF:
+                        return (left + 1)/(double)(data.Length);
+                    default:
+                    {
+                        var a = left/(double)(data.Length - 1);
+                        var b = right/(double)(data.Length - 1);
+                        return ((data[right] - x)*a + (x - data[left])*b)/(data[right] - data[left]);
+                    }
+                }
+            }
+        }
+
         /// <summary>
         /// Evaluates the rank of each entry of the sorted data array (ascending).
         /// The rank definition can be specificed to be compatible
diff --git a/src/Numerics/Statistics/Statistics.cs b/src/Numerics/Statistics/Statistics.cs
index b10c0c13..d752ff5b 100644
--- a/src/Numerics/Statistics/Statistics.cs
+++ b/src/Numerics/Statistics/Statistics.cs
@@ -370,51 +370,7 @@ namespace MathNet.Numerics.Statistics
         }
 
         /// <summary>
-        /// Estimates the empirical inverse CDF at tau from the provided samples.
-        /// </summary>
-        /// <param name="data">The data sample sequence.</param>
-        /// <param name="tau">Quantile selector, between 0.0 and 1.0 (inclusive).</param>
-        public static double InverseCDF(this IEnumerable<double> data, double tau)
-        {
-            var array = data.ToArray();
-            return ArrayStatistics.QuantileCustomInplace(array, tau, QuantileDefinition.InverseCDF);
-        }
-
-        /// <summary>
-        /// Estimates the empirical inverse CDF at tau from the provided samples.
-        /// </summary>
-        /// <param name="data">The data sample sequence.</param>
-        /// <param name="tau">Quantile selector, between 0.0 and 1.0 (inclusive).</param>
-        public static double InverseCDF(this IEnumerable<double?> data, double tau)
-        {
-            var array = data.Where(d => d.HasValue).Select(d => d.Value).ToArray();
-            return ArrayStatistics.QuantileCustomInplace(array, tau, QuantileDefinition.InverseCDF);
-        }
-
-        /// <summary>
-        /// Estimates the empirical inverse CDF at tau from the provided samples.
-        /// </summary>
-        /// <param name="data">The data sample sequence.</param>
-        public static Func<double, double> InverseCDFFunc(this IEnumerable<double> data)
-        {
-            var array = data.ToArray();
-            Array.Sort(array);
-            return tau => SortedArrayStatistics.QuantileCustom(array, tau, QuantileDefinition.InverseCDF);
-        }
-
-        /// <summary>
-        /// Estimates the empirical inverse CDF at tau from the provided samples.
-        /// </summary>
-        /// <param name="data">The data sample sequence.</param>
-        public static Func<double, double> InverseCDFFunc(this IEnumerable<double?> data)
-        {
-            var array = data.Where(d => d.HasValue).Select(d => d.Value).ToArray();
-            Array.Sort(array);
-            return tau => SortedArrayStatistics.QuantileCustom(array, tau, QuantileDefinition.InverseCDF);
-        }
-
-        /// <summary>
-        /// stimates the tau-th quantile from the provided samples.
+        /// Estimates the tau-th quantile from the provided samples.
         /// The tau-th quantile is the data value where the cumulative distribution
         /// function crosses tau. The quantile definition can be specificed to be compatible
         /// with an existing system.
@@ -429,7 +385,7 @@ namespace MathNet.Numerics.Statistics
         }
 
         /// <summary>
-        /// stimates the tau-th quantile from the provided samples.
+        /// Estimates the tau-th quantile from the provided samples.
         /// The tau-th quantile is the data value where the cumulative distribution
         /// function crosses tau. The quantile definition can be specificed to be compatible
         /// with an existing system.
@@ -444,7 +400,7 @@ namespace MathNet.Numerics.Statistics
         }
 
         /// <summary>
-        /// stimates the tau-th quantile from the provided samples.
+        /// Estimates the tau-th quantile from the provided samples.
         /// The tau-th quantile is the data value where the cumulative distribution
         /// function crosses tau. The quantile definition can be specificed to be compatible
         /// with an existing system.
@@ -459,7 +415,7 @@ namespace MathNet.Numerics.Statistics
         }
 
         /// <summary>
-        /// stimates the tau-th quantile from the provided samples.
+        /// Estimates the tau-th quantile from the provided samples.
         /// The tau-th quantile is the data value where the cumulative distribution
         /// function crosses tau. The quantile definition can be specificed to be compatible
         /// with an existing system.
@@ -635,13 +591,14 @@ namespace MathNet.Numerics.Statistics
             return order => SortedArrayStatistics.OrderStatistic(array, order);
         }
 
+
         /// <summary>
         /// Evaluates the rank of each entry of the provided samples.
         /// The rank definition can be specificed to be compatible
         /// with an existing system.
         /// </summary>
         /// <param name="data">The data sample sequence.</param>
-        /// <param name="definition">Rank definition, to choose how ties should be handled.</param>
+        /// <param name="definition">Rank definition, to choose how ties should be handled and what product/definition it should be consistent with</param>
         public static double[] Ranks(this IEnumerable<double> data, RankDefinition definition = RankDefinition.Default)
         {
             var array = data.ToArray();
@@ -654,11 +611,154 @@ namespace MathNet.Numerics.Statistics
         /// with an existing system.
         /// </summary>
         /// <param name="data">The data sample sequence.</param>
-        /// <param name="definition">Rank definition, to choose how ties should be handled.</param>
+        /// <param name="definition">Rank definition, to choose how ties should be handled and what product/definition it should be consistent with</param>
         public static double[] Ranks(this IEnumerable<double?> data, RankDefinition definition = RankDefinition.Default)
         {
-            var array = data.Where(d => d.HasValue).Select(d => d.Value).ToArray();
-            return ArrayStatistics.RanksInplace(array, definition);
+            return Ranks(data.Where(d => d.HasValue).Select(d => d.Value), definition);
+        }
+
+
+        /// <summary>
+        /// Estimates the quantile tau from the provided samples.
+        /// The tau-th quantile is the data value where the cumulative distribution
+        /// function crosses tau. The quantile definition can be specificed to be compatible
+        /// with an existing system.
+        /// </summary>
+        /// <param name="data">The data sample sequence.</param>
+        /// <param name="x">Quantile value.</param>
+        /// <param name="definition">Rank definition, to choose how ties should be handled and what product/definition it should be consistent with</param>
+        public static double QuantileRank(this IEnumerable<double> data, double x, RankDefinition definition = RankDefinition.Default)
+        {
+            var array = data.ToArray();
+            Array.Sort(array);
+            return SortedArrayStatistics.QuantileRank(array, x, definition);
+        }
+
+        /// <summary>
+        /// Estimates the quantile tau from the provided samples.
+        /// The tau-th quantile is the data value where the cumulative distribution
+        /// function crosses tau. The quantile definition can be specificed to be compatible
+        /// with an existing system.
+        /// </summary>
+        /// <param name="data">The data sample sequence.</param>
+        /// <param name="x">Quantile value.</param>
+        /// <param name="definition">Rank definition, to choose how ties should be handled and what product/definition it should be consistent with</param>
+        public static double QuantileRank(this IEnumerable<double?> data, double x, RankDefinition definition = RankDefinition.Default)
+        {
+            return QuantileRank(data.Where(d => d.HasValue).Select(d => d.Value), x, definition);
+        }
+
+        /// <summary>
+        /// Estimates the quantile tau from the provided samples.
+        /// The tau-th quantile is the data value where the cumulative distribution
+        /// function crosses tau. The quantile definition can be specificed to be compatible
+        /// with an existing system.
+        /// </summary>
+        /// <param name="data">The data sample sequence.</param>
+        /// <param name="definition">Rank definition, to choose how ties should be handled and what product/definition it should be consistent with</param>
+        public static Func<double, double> QuantileRankFunc(this IEnumerable<double> data, RankDefinition definition = RankDefinition.Default)
+        {
+            var array = data.ToArray();
+            Array.Sort(array);
+            return x => SortedArrayStatistics.QuantileRank(array, x, definition);
+        }
+
+        /// <summary>
+        /// Estimates the quantile tau from the provided samples.
+        /// The tau-th quantile is the data value where the cumulative distribution
+        /// function crosses tau. The quantile definition can be specificed to be compatible
+        /// with an existing system.
+        /// </summary>
+        /// <param name="data">The data sample sequence.</param>
+        /// <param name="definition">Rank definition, to choose how ties should be handled and what product/definition it should be consistent with</param>
+        public static Func<double, double> QuantileRankFunc(this IEnumerable<double?> data, RankDefinition definition = RankDefinition.Default)
+        {
+            return QuantileRankFunc(data.Where(d => d.HasValue).Select(d => d.Value), definition);
+        }
+
+
+        /// <summary>
+        /// Estimates the empirical cummulative distribution function (CDF) at x from the provided samples.
+        /// </summary>
+        /// <param name="data">The data sample sequence.</param>
+        /// <param name="x">The value where to estimate the CDF at.</param>
+        public static double EmpiricalCDF(this IEnumerable<double> data, double x)
+        {
+            var array = data.ToArray();
+            Array.Sort(array);
+            return SortedArrayStatistics.EmpiricalCDF(array, x);
+        }
+
+        /// <summary>
+        /// Estimates the empirical cummulative distribution function (CDF) at x from the provided samples.
+        /// </summary>
+        /// <param name="data">The data sample sequence.</param>
+        /// <param name="x">The value where to estimate the CDF at.</param>
+        public static double EmpiricalCDF(this IEnumerable<double?> data, double x)
+        {
+            return EmpiricalCDF(data.Where(d => d.HasValue).Select(d => d.Value), x);
+        }
+
+        /// <summary>
+        /// Estimates the empirical cummulative distribution function (CDF) at x from the provided samples.
+        /// </summary>
+        /// <param name="data">The data sample sequence.</param>
+        public static Func<double, double> EmpiricalCDFFunc(this IEnumerable<double> data)
+        {
+            var array = data.ToArray();
+            Array.Sort(array);
+            return x => SortedArrayStatistics.EmpiricalCDF(array, x);
+        }
+
+        /// <summary>
+        /// Estimates the empirical cummulative distribution function (CDF) at x from the provided samples.
+        /// </summary>
+        /// <param name="data">The data sample sequence.</param>
+        public static Func<double, double> EmpiricalCDFFunc(this IEnumerable<double?> data)
+        {
+            return EmpiricalCDFFunc(data.Where(d => d.HasValue).Select(d => d.Value));
+        }
+
+
+        /// <summary>
+        /// Estimates the empirical inverse CDF at tau from the provided samples.
+        /// </summary>
+        /// <param name="data">The data sample sequence.</param>
+        /// <param name="tau">Quantile selector, between 0.0 and 1.0 (inclusive).</param>
+        public static double InverseCDF(this IEnumerable<double> data, double tau)
+        {
+            var array = data.ToArray();
+            return ArrayStatistics.QuantileCustomInplace(array, tau, QuantileDefinition.InverseCDF);
+        }
+
+        /// <summary>
+        /// Estimates the empirical inverse CDF at tau from the provided samples.
+        /// </summary>
+        /// <param name="data">The data sample sequence.</param>
+        /// <param name="tau">Quantile selector, between 0.0 and 1.0 (inclusive).</param>
+        public static double InverseCDF(this IEnumerable<double?> data, double tau)
+        {
+            return InverseCDF(data.Where(d => d.HasValue).Select(d => d.Value), tau);
+        }
+
+        /// <summary>
+        /// Estimates the empirical inverse CDF at tau from the provided samples.
+        /// </summary>
+        /// <param name="data">The data sample sequence.</param>
+        public static Func<double, double> InverseCDFFunc(this IEnumerable<double> data)
+        {
+            var array = data.ToArray();
+            Array.Sort(array);
+            return tau => SortedArrayStatistics.QuantileCustom(array, tau, QuantileDefinition.InverseCDF);
+        }
+
+        /// <summary>
+        /// Estimates the empirical inverse CDF at tau from the provided samples.
+        /// </summary>
+        /// <param name="data">The data sample sequence.</param>
+        public static Func<double, double> InverseCDFFunc(this IEnumerable<double?> data)
+        {
+            return InverseCDFFunc(data.Where(d => d.HasValue).Select(d => d.Value));
         }
     }
 }
diff --git a/src/UnitTests/ExcelTests.cs b/src/UnitTests/ExcelTests.cs
index 1280a5b8..73efe30a 100644
--- a/src/UnitTests/ExcelTests.cs
+++ b/src/UnitTests/ExcelTests.cs
@@ -102,6 +102,38 @@ namespace MathNet.Numerics.UnitTests
             Assert.That(ExcelFunctions.QUARTILE(array, 3), Is.EqualTo(9.25000000000).Within(1e-8));
             Assert.That(ExcelFunctions.QUARTILE(array, 4), Is.EqualTo(12.00000000000).Within(1e-8));
         }
+
+        [Test]
+        public void PERCENTRANK()
+        {
+            var array = new Double[] { 1, 8, 12, 7, 2, 9, 10, 4 };
+            Assert.That(ExcelFunctions.PERCENTRANK(array, 1.0), Is.EqualTo(0.00000000000).Within(1e-8), "A1");
+            Assert.That(ExcelFunctions.PERCENTRANK(array, 2.0), Is.EqualTo(0.14285714280).Within(1e-8), "A2");
+            Assert.That(ExcelFunctions.PERCENTRANK(array, 3.0), Is.EqualTo(0.21428571420).Within(1e-8), "A3");
+            Assert.That(ExcelFunctions.PERCENTRANK(array, 4.0), Is.EqualTo(0.28571428570).Within(1e-8), "A4");
+            Assert.That(ExcelFunctions.PERCENTRANK(array, 5.0), Is.EqualTo(0.33333333330).Within(1e-8), "A5");
+            Assert.That(ExcelFunctions.PERCENTRANK(array, 6.0), Is.EqualTo(0.38095238090).Within(1e-8), "A6");
+            Assert.That(ExcelFunctions.PERCENTRANK(array, 7.0), Is.EqualTo(0.42857142850).Within(1e-8), "A7");
+            Assert.That(ExcelFunctions.PERCENTRANK(array, 8.0), Is.EqualTo(0.57142857140).Within(1e-8), "A8");
+            Assert.That(ExcelFunctions.PERCENTRANK(array, 9.0), Is.EqualTo(0.71428571420).Within(1e-8), "A9");
+            Assert.That(ExcelFunctions.PERCENTRANK(array, 10.0), Is.EqualTo(0.85714285710).Within(1e-8), "A10");
+            Assert.That(ExcelFunctions.PERCENTRANK(array, 11.0), Is.EqualTo(0.92857142850).Within(1e-8), "A11");
+            Assert.That(ExcelFunctions.PERCENTRANK(array, 12.0), Is.EqualTo(1.00000000000).Within(1e-8), "A12");
+
+            array = new Double[] { 1, 9, 12, 7, 2, 9, 10, 2 };
+            Assert.That(ExcelFunctions.PERCENTRANK(array, 1.0), Is.EqualTo(0.00000000000).Within(1e-8), "B1");
+            Assert.That(ExcelFunctions.PERCENTRANK(array, 2.0), Is.EqualTo(0.14285714280).Within(1e-8), "B2");
+            Assert.That(ExcelFunctions.PERCENTRANK(array, 3.0), Is.EqualTo(0.31428571420).Within(1e-8), "B3");
+            Assert.That(ExcelFunctions.PERCENTRANK(array, 4.0), Is.EqualTo(0.34285714280).Within(1e-8), "B4");
+            Assert.That(ExcelFunctions.PERCENTRANK(array, 5.0), Is.EqualTo(0.37142857140).Within(1e-8), "B5");
+            Assert.That(ExcelFunctions.PERCENTRANK(array, 6.0), Is.EqualTo(0.40000000000).Within(1e-8), "B6");
+            Assert.That(ExcelFunctions.PERCENTRANK(array, 7.0), Is.EqualTo(0.42857142850).Within(1e-8), "B7");
+            Assert.That(ExcelFunctions.PERCENTRANK(array, 8.0), Is.EqualTo(0.50000000000).Within(1e-8), "B8");
+            Assert.That(ExcelFunctions.PERCENTRANK(array, 9.0), Is.EqualTo(0.57142857140).Within(1e-8), "B9");
+            Assert.That(ExcelFunctions.PERCENTRANK(array, 10.0), Is.EqualTo(0.85714285710).Within(1e-8), "B10");
+            Assert.That(ExcelFunctions.PERCENTRANK(array, 11.0), Is.EqualTo(0.92857142850).Within(1e-8), "B11");
+            Assert.That(ExcelFunctions.PERCENTRANK(array, 12.0), Is.EqualTo(1.00000000000).Within(1e-8), "B12");
+        }
     }
 }
 // ReSharper restore InconsistentNaming
diff --git a/src/UnitTests/StatisticsTests/StatisticsTests.cs b/src/UnitTests/StatisticsTests/StatisticsTests.cs
index 725d8f4e..16837ca8 100644
--- a/src/UnitTests/StatisticsTests/StatisticsTests.cs
+++ b/src/UnitTests/StatisticsTests/StatisticsTests.cs
@@ -65,7 +65,6 @@ namespace MathNet.Numerics.UnitTests.StatisticsTests
         {
             double[] data = null;
 
-            // ReSharper disable InvokeAsExtensionMethod
             Assert.That(() => Statistics.Minimum(data), Throws.Exception);
             Assert.That(() => Statistics.Maximum(data), Throws.Exception);
             Assert.That(() => Statistics.Mean(data), Throws.Exception);
@@ -77,7 +76,6 @@ namespace MathNet.Numerics.UnitTests.StatisticsTests
             Assert.That(() => Statistics.PopulationStandardDeviation(data), Throws.Exception);
             Assert.That(() => Statistics.Covariance(data, data), Throws.Exception);
             Assert.That(() => Statistics.PopulationCovariance(data, data), Throws.Exception);
-            // ReSharper restore InvokeAsExtensionMethod
 
             Assert.That(() => SortedArrayStatistics.Minimum(data), Throws.Exception.TypeOf<NullReferenceException>());
             Assert.That(() => SortedArrayStatistics.Minimum(data), Throws.Exception.TypeOf<NullReferenceException>());
@@ -659,6 +657,69 @@ namespace MathNet.Numerics.UnitTests.StatisticsTests
                 Is.EqualTo(new[] { 1.0, 5, 8, 4, 2, 6, 7, 3 }).AsCollection.Within(1e-8));
         }
 
+        [Test]
+        public void EmpiricalCDF()
+        {
+            // R: ecdf(data)(x)
+            var ties = new double[] { 1, 9, 12, 7, 2, 9, 10, 2 };
+
+            Assert.That(Statistics.EmpiricalCDF(ties, -1.0), Is.EqualTo(0.0).Within(1e-8));
+            Assert.That(Statistics.EmpiricalCDF(ties, 0.0), Is.EqualTo(0.0).Within(1e-8));
+            Assert.That(Statistics.EmpiricalCDF(ties, 1.0), Is.EqualTo(0.125).Within(1e-8));
+            Assert.That(Statistics.EmpiricalCDF(ties, 2.0), Is.EqualTo(0.375).Within(1e-8));
+            Assert.That(Statistics.EmpiricalCDF(ties, 3.0), Is.EqualTo(0.375).Within(1e-8));
+            Assert.That(Statistics.EmpiricalCDF(ties, 4.0), Is.EqualTo(0.375).Within(1e-8));
+            Assert.That(Statistics.EmpiricalCDF(ties, 5.0), Is.EqualTo(0.375).Within(1e-8));
+            Assert.That(Statistics.EmpiricalCDF(ties, 6.0), Is.EqualTo(0.375).Within(1e-8));
+            Assert.That(Statistics.EmpiricalCDF(ties, 7.0), Is.EqualTo(0.5).Within(1e-8));
+            Assert.That(Statistics.EmpiricalCDF(ties, 8.0), Is.EqualTo(0.5).Within(1e-8));
+            Assert.That(Statistics.EmpiricalCDF(ties, 9.0), Is.EqualTo(0.75).Within(1e-8));
+            Assert.That(Statistics.EmpiricalCDF(ties, 10.0), Is.EqualTo(0.875).Within(1e-8));
+            Assert.That(Statistics.EmpiricalCDF(ties, 11.0), Is.EqualTo(0.875).Within(1e-8));
+            Assert.That(Statistics.EmpiricalCDF(ties, 12.0), Is.EqualTo(1.0).Within(1e-8));
+            Assert.That(Statistics.EmpiricalCDF(ties, 13.0), Is.EqualTo(1.0).Within(1e-8));
+        }
+
+        [Test]
+        public void EmpiricalCDFSortedArray()
+        {
+            // R: ecdf(data)(x)
+            var ties = new double[] { 1, 9, 12, 7, 2, 9, 10, 2 };
+            Array.Sort(ties);
+
+            Assert.That(SortedArrayStatistics.EmpiricalCDF(ties, -1.0), Is.EqualTo(0.0).Within(1e-8));
+            Assert.That(SortedArrayStatistics.EmpiricalCDF(ties, 0.0), Is.EqualTo(0.0).Within(1e-8));
+            Assert.That(SortedArrayStatistics.EmpiricalCDF(ties, 1.0), Is.EqualTo(0.125).Within(1e-8));
+            Assert.That(SortedArrayStatistics.EmpiricalCDF(ties, 2.0), Is.EqualTo(0.375).Within(1e-8));
+            Assert.That(SortedArrayStatistics.EmpiricalCDF(ties, 3.0), Is.EqualTo(0.375).Within(1e-8));
+            Assert.That(SortedArrayStatistics.EmpiricalCDF(ties, 4.0), Is.EqualTo(0.375).Within(1e-8));
+            Assert.That(SortedArrayStatistics.EmpiricalCDF(ties, 5.0), Is.EqualTo(0.375).Within(1e-8));
+            Assert.That(SortedArrayStatistics.EmpiricalCDF(ties, 6.0), Is.EqualTo(0.375).Within(1e-8));
+            Assert.That(SortedArrayStatistics.EmpiricalCDF(ties, 7.0), Is.EqualTo(0.5).Within(1e-8));
+            Assert.That(SortedArrayStatistics.EmpiricalCDF(ties, 8.0), Is.EqualTo(0.5).Within(1e-8));
+            Assert.That(SortedArrayStatistics.EmpiricalCDF(ties, 9.0), Is.EqualTo(0.75).Within(1e-8));
+            Assert.That(SortedArrayStatistics.EmpiricalCDF(ties, 10.0), Is.EqualTo(0.875).Within(1e-8));
+            Assert.That(SortedArrayStatistics.EmpiricalCDF(ties, 11.0), Is.EqualTo(0.875).Within(1e-8));
+            Assert.That(SortedArrayStatistics.EmpiricalCDF(ties, 12.0), Is.EqualTo(1.0).Within(1e-8));
+            Assert.That(SortedArrayStatistics.EmpiricalCDF(ties, 13.0), Is.EqualTo(1.0).Within(1e-8));
+
+            Assert.That(SortedArrayStatistics.QuantileRank(ties, -1.0, RankDefinition.EmpiricalCDF), Is.EqualTo(0.0).Within(1e-8));
+            Assert.That(SortedArrayStatistics.QuantileRank(ties, 0.0, RankDefinition.EmpiricalCDF), Is.EqualTo(0.0).Within(1e-8));
+            Assert.That(SortedArrayStatistics.QuantileRank(ties, 1.0, RankDefinition.EmpiricalCDF), Is.EqualTo(0.125).Within(1e-8));
+            Assert.That(SortedArrayStatistics.QuantileRank(ties, 2.0, RankDefinition.EmpiricalCDF), Is.EqualTo(0.375).Within(1e-8));
+            Assert.That(SortedArrayStatistics.QuantileRank(ties, 3.0, RankDefinition.EmpiricalCDF), Is.EqualTo(0.375).Within(1e-8));
+            Assert.That(SortedArrayStatistics.QuantileRank(ties, 4.0, RankDefinition.EmpiricalCDF), Is.EqualTo(0.375).Within(1e-8));
+            Assert.That(SortedArrayStatistics.QuantileRank(ties, 5.0, RankDefinition.EmpiricalCDF), Is.EqualTo(0.375).Within(1e-8));
+            Assert.That(SortedArrayStatistics.QuantileRank(ties, 6.0, RankDefinition.EmpiricalCDF), Is.EqualTo(0.375).Within(1e-8));
+            Assert.That(SortedArrayStatistics.QuantileRank(ties, 7.0, RankDefinition.EmpiricalCDF), Is.EqualTo(0.5).Within(1e-8));
+            Assert.That(SortedArrayStatistics.QuantileRank(ties, 8.0, RankDefinition.EmpiricalCDF), Is.EqualTo(0.5).Within(1e-8));
+            Assert.That(SortedArrayStatistics.QuantileRank(ties, 9.0, RankDefinition.EmpiricalCDF), Is.EqualTo(0.75).Within(1e-8));
+            Assert.That(SortedArrayStatistics.QuantileRank(ties, 10.0, RankDefinition.EmpiricalCDF), Is.EqualTo(0.875).Within(1e-8));
+            Assert.That(SortedArrayStatistics.QuantileRank(ties, 11.0, RankDefinition.EmpiricalCDF), Is.EqualTo(0.875).Within(1e-8));
+            Assert.That(SortedArrayStatistics.QuantileRank(ties, 12.0, RankDefinition.EmpiricalCDF), Is.EqualTo(1.0).Within(1e-8));
+            Assert.That(SortedArrayStatistics.QuantileRank(ties, 13.0, RankDefinition.EmpiricalCDF), Is.EqualTo(1.0).Within(1e-8));
+        }
+
         [Test]
         public void MedianOnShortSequence()
         {