Some bug fixes on Binomial, Categorical and Multinomial distributions.

src/Numerics/Distributions/Discrete/Binomial.cs

@@ -0,0 +1,391 @@
+// <copyright file="Binomial.cs" company="Math.NET">
+// Math.NET Numerics, part of the Math.NET Project
+// http://mathnet.opensourcedotnet.info
+//
+// Copyright (c) 2009 Math.NET
+//
+// Permission is hereby granted, free of charge, to any person
+// obtaining a copy of this software and associated documentation
+// files (the "Software"), to deal in the Software without
+// restriction, including without limitation the rights to use,
+// copy, modify, merge, publish, distribute, sublicense, and/or sell
+// copies of the Software, and to permit persons to whom the
+// Software is furnished to do so, subject to the following
+// conditions:
+//
+// The above copyright notice and this permission notice shall be
+// included in all copies or substantial portions of the Software.
+//
+// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+// OTHER DEALINGS IN THE SOFTWARE.
+// </copyright>
+
+namespace MathNet.Numerics.Distributions
+{
+    using System;
+    using System.Collections.Generic;
+    using Properties;
+
+
+    /// <summary>
+    /// Implements the binomial distribution. For details about this distribution, see 
+    /// <a href="http://en.wikipedia.org/wiki/Binomial_distribution">Wikipedia - Binomial distribution</a>.
+    /// </summary>
+    /// <remarks><para>The distribution is parameterized by a probability (between 0.0 and 1.0).</para>
+    /// <para>The distribution will use the <see cref="System.Random"/> by default. 
+    /// Users can set the random number generator by using the <see cref="RandomSource"/> property.</para>
+    /// <para>The statistics classes will check all the incoming parameters whether they are in the allowed
+    /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters
+    /// to false, all parameter checks can be turned off.</para></remarks>
+    public class Binomial : IDiscreteDistribution
+    {
+        /// <summary>
+        /// Stores the normalized binomial probability.
+        /// </summary>
+        private double _p;
+
+        /// <summary>
+        /// The number of trials.
+        /// </summary>
+        private int _n;
+
+        /// <summary>
+        /// The distribution's random number generator.
+        /// </summary>
+        private Random _random;
+
+        /// <summary>
+        /// Initializes a new instance of the Binomial class.
+        /// </summary>
+        /// <param name="p">The success probability of a trial.</param>
+        /// <param name="n">The number of trials.</param>
+        /// <exception cref="ArgumentOutOfRangeException">If <paramref name="p"/> is not in the interval [0.0,1.0].</exception>
+        /// <exception cref="ArgumentOutOfRangeException">If <paramref name="n"/> is negative.</exception>
+        public Binomial(double p, int n)
+        {
+            SetParameters(p, n);
+            RandomSource = new System.Random();
+        }
+
+        /// <summary>
+        /// A string representation of the distribution.
+        /// </summary>
+        public override string ToString()
+        {
+            return "Binomial(Success Probability = " + _p + ", Number of Trials = " + _n + ")";
+        }
+
+        /// <summary>
+        /// Checks whether the parameters of the distribution are valid. 
+        /// </summary>
+        /// <param name="p">The success probability of a trial.</param>
+        /// <param name="n">The number of trials.</param>
+        /// <returns>false <paramref name="p"/> is not in the interval [0.0,1.0] or <paramref name="n"/> is negative, true otherwise.</exception>
+        private static bool IsValidParameterSet(double p, int n)
+        {
+            if(p < 0.0 || p > 1.0)
+            {
+                return false;
+            }
+
+            if(n < 0)
+            {
+                return false;
+            }
+
+            return true;
+        }
+
+        /// <summary>
+        /// Sets the parameters of the distribution after checking their validity.
+        /// </summary>
+        /// <param name="p">The success probability of a trial.</param>
+        /// <param name="n">The number of trials.</param>
+        /// <exception cref="ArgumentOutOfRangeException">If <paramref name="p"/> is not in the interval [0.0,1.0].</exception>
+        /// <exception cref="ArgumentOutOfRangeException">If <paramref name="n"/> is negative.</exception>
+        private void SetParameters(double p, int n)
+        {
+            if (Control.CheckDistributionParameters && !IsValidParameterSet(p, n))
+            {
+                throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters);
+            }
+
+            _p = p;
+            _n = n;
+        }
+
+        /// <summary>
+        /// Gets or sets the success probability.
+        /// </summary>
+        public double P
+        {
+            get
+            {
+                return _p;
+            }
+
+            set
+            {
+                SetParameters(value, _n);
+            }
+        }
+
+        /// <summary>
+        /// Gets or sets the number of trials.
+        /// </summary>
+        public int N
+        {
+            get
+            {
+                return _n;
+            }
+
+            set
+            {
+                SetParameters(_p, value);
+            }
+        }
+
+        #region IDistribution Members
+
+        /// <summary>
+        /// Gets or sets the random number generator which is used to draw random samples.
+        /// </summary>
+        public Random RandomSource
+        {
+            get
+            {
+                return _random;
+            }
+
+            set
+            {
+                if (value == null)
+                {
+                    throw new ArgumentNullException();
+                }
+
+                _random = value;
+            }
+        }
+
+        /// <summary>
+        /// Gets the mean of the distribution.
+        /// </summary>
+        public double Mean
+        {
+            get { return _p * _n; }
+        }
+
+        /// <summary>
+        /// Gets the standard deviation of the distribution.
+        /// </summary>
+        public double StdDev
+        {
+            get { return Math.Sqrt(_p * (1.0 - _p) * _n); }
+        }
+
+        /// <summary>
+        /// Gets the variance of the distribution.
+        /// </summary>
+        public double Variance
+        {
+            get { return _p * (1.0 - _p) * _n; }
+        }
+
+        /// <summary>
+        /// Gets the entropy of the distribution.
+        /// </summary>
+        public double Entropy
+        {
+            get
+            {
+                double E = 0.0;
+                for(int i = 0; i < _n; i++)
+                {
+                    double p = Probability(i);
+                    E += p * Math.Log(p);
+                }
+                return E;
+            }
+        }
+
+        /// <summary>
+        /// Gets the skewness of the distribution.
+        /// </summary>
+        public double Skewness
+        {
+            get { return (1.0 - 2.0 * _p) / Math.Sqrt(_n * _p * (1.0 - _p)); }
+        }
+
+        /// <summary>
+        /// Gets the smallest element in the domain of the distributions which can be represented by an integer.
+        /// </summary>
+        public int Minimum { get { return 0; } }
+
+        /// <summary>
+        /// Gets the largest element in the domain of the distributions which can be represented by an integer.
+        /// </summary>
+        public int Maximum { get { return _n; } }
+
+        /// <summary>
+        /// Computes the cumulative distribution function of the Binomial distribution.
+        /// </summary>
+        /// <param name="x">The location at which to compute the cumulative density.</param>
+        /// <returns>the cumulative density at <paramref name="x"/>.</returns>
+        public double CumulativeDistribution(double x)
+        {
+            if (x < 0.0)
+            {
+                return 0.0;
+            }
+            else if (x > _n)
+            {
+                return 1.0;
+            }
+
+            int k = (int) Math.Floor(x);
+            return (_n - k) * Combinatorics.Combinations(_n,k) * SpecialFunctions.BetaRegularized(_n - k, 1 + k, 1-_p);
+        }
+
+        #endregion
+
+        #region IDiscreteDistribution Members
+
+        /// <summary>
+        /// The mode of the distribution.
+        /// </summary>
+        public int Mode
+        {
+            get { return (int) Math.Floor((_n + 1) * _p); }
+        }
+
+        /// <summary>
+        /// The median of the distribution.
+        /// </summary>
+        public int Median
+        {
+            get { throw new NotImplementedException(); }
+        }
+
+        /// <summary>
+        /// Computes the probability of a specific value.
+        /// </summary>
+        public double Probability(int val)
+        {
+            if (val < 0)
+            {
+                return 0.0;
+            }
+
+            if (val > _n)
+            {
+                return 0.0;
+            }
+
+            return SpecialFunctions.Binomial(_n, val) * Math.Pow(_p, val) * Math.Pow(1.0 - _p, _n - val);
+        }
+
+        /// <summary>
+        /// Computes the probability of a specific value.
+        /// </summary>
+        public double ProbabilityLn(int val)
+        {
+            if (val < 0)
+            {
+                return 0.0;
+            }
+
+            if (val > _n)
+            {
+                return 0.0;
+            }
+
+            return SpecialFunctions.BinomialLn(_n, val) + val * Math.Log(_p) + (_n - val) * Math.Log(1.0 - _p);
+        }
+
+        /// <summary>
+        /// Samples a Binomially distributed random variable.
+        /// </summary>
+        /// <returns>The number of successful trials.</returns>
+        public int Sample()
+        {
+            return DoSample(RandomSource, _p, _n);
+        }
+
+        /// <summary>
+        /// Samples an array of Bernoulli distributed random variables.
+        /// </summary>
+        /// <returns>a sequence of successful trial counts.</returns>
+        public IEnumerable<int> Samples()
+        {
+            while (true)
+            {
+                yield return DoSample(RandomSource, _p, _n);
+            }
+        }
+
+        #endregion
+
+        /// <summary>
+        /// Samples a binomially distributed random variable.
+        /// </summary>
+        /// <param name="rnd">The random number generator to use.</param>
+        /// <param name="p">The success probability of a trial; must be in the interval [0.0, 1.0].</param>
+        /// <param name="n">The number of trials; must be positive.</param>
+        /// <returns>The number of successes in <see cref="N"/> trials.</returns>
+        public static int Sample(System.Random rnd, double p, int n)
+        {
+            if (Control.CheckDistributionParameters && !IsValidParameterSet(p, n))
+            {
+                throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters);
+            }
+
+            return DoSample(rnd, p, n);
+        }
+
+        /// <summary>
+        /// Samples a sequence of binomially distributed random variable.
+        /// </summary>
+        /// <param name="rnd">The random number generator to use.</param>
+        /// <param name="p">The success probability of a trial; must be in the interval [0.0, 1.0].</param>
+        /// <param name="n">The number of trials; must be positive.</param>
+        /// <returns>a sequence of successful trial counts.</returns>
+        public static IEnumerable<int> Samples(System.Random rnd, double p, int n)
+        {
+            if (Control.CheckDistributionParameters && !IsValidParameterSet(p, n))
+            {
+                throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters);
+            }
+
+            while (true)
+            {
+                yield return DoSample(rnd, p, n);
+            }
+        }
+
+        /// <summary>
+        /// Generates a sample from the Binomial distribution without doing parameter checking.
+        /// </summary>
+        /// <param name="rnd">The random number generator to use.</param>
+        /// <param name="p">The success probability of a trial; must be in the interval [0.0, 1.0].</param>
+        /// <param name="n">The number of trials; must be positive.</param>
+        /// <returns>The number of successful trials.</returns>
+        private static int DoSample(System.Random rnd, double p, int n)
+        {
+            int k = 0;
+            for (int i = 0; i < n; i++)
+            {
+                k += (rnd.NextDouble() < p ? 1 : 0);
+            }
+
+            return k;
+        }
+    }
+}

src/Numerics/Distributions/Discrete/Categorical.cs

@@ -0,0 +1,422 @@
+// <copyright file="Categorical.cs" company="Math.NET">
+// Math.NET Numerics, part of the Math.NET Project
+// http://mathnet.opensourcedotnet.info
+//
+// Copyright (c) 2009 Math.NET
+//
+// Permission is hereby granted, free of charge, to any person
+// obtaining a copy of this software and associated documentation
+// files (the "Software"), to deal in the Software without
+// restriction, including without limitation the rights to use,
+// copy, modify, merge, publish, distribute, sublicense, and/or sell
+// copies of the Software, and to permit persons to whom the
+// Software is furnished to do so, subject to the following
+// conditions:
+//
+// The above copyright notice and this permission notice shall be
+// included in all copies or substantial portions of the Software.
+//
+// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+// OTHER DEALINGS IN THE SOFTWARE.
+// </copyright>
+
+namespace MathNet.Numerics.Distributions
+{
+    using System;
+    using System.Collections.Generic;
+    using Properties;
+    using MathNet.Numerics.Statistics;
+
+
+    /// <summary>
+    /// Implements the categorical distribution. For details about this distribution, see 
+    /// <a href="http://en.wikipedia.org/wiki/Categorical_distribution">Wikipedia - Categorical distribution</a>. This
+    /// distribution is sometimes called the Discrete distribution.
+    /// </summary>
+    /// <remarks><para>The distribution is parameterized by a vector of ratios: in other words, the parameter
+    /// does not have to be normalized and sum to 1. The reason is that some vectors can't be exactly normalized
+    /// to sum to 1 in floating point representation.</para>
+    /// <para>The distribution will use the <see cref="System.Random"/> by default. 
+    /// Users can set the random number generator by using the <see cref="RandomSource"/> property.</para>
+    /// <para>The statistics classes will check all the incoming parameters whether they are in the allowed
+    /// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters
+    /// to false, all parameter checks can be turned off.</para></remarks>
+    public class Categorical : IDiscreteDistribution
+    {
+        /// <summary>
+        /// Stores the normalized categorical probabilities.
+        /// </summary>
+        private double[] _p;
+
+        /// <summary>
+        /// The distribution's random number generator.
+        /// </summary>
+        private Random _random;
+
+        /// <summary>
+        /// Initializes a new instance of the Categorical class.
+        /// </summary>
+        /// <param name="p">An array of nonnegative ratios: this array does not need to be normalized 
+        /// as this is often impossible using floating point arithmetic.</param>
+        /// <exception cref="ArgumentException">If any of the probabilities are negative or do not sum to one.</exception>
+        public Categorical(double[] p)
+        {
+            SetParameters(p);
+            RandomSource = new System.Random();
+        }
+
+        /* TODO
+        /// <summary>
+        /// Generate a categorical distribution from histogram <paramref name="h"/>. The distribution will
+        /// not be automatically updated when the histogram changes.
+        /// </summary>
+        public Categorical(Histogram h)
+        {
+            // The probability distribution vector.
+            _p = new double[h.BinCount];
+
+            // Fill in the distribution vector.
+            for (int i = 0; i < h.BinCount; i++)
+            {
+                _p[i] = h[i];
+            }
+
+            RandomNumberGenerator = new System.Random();
+        }*/
+
+        /// <summary>
+        /// A string representation of the distribution.
+        /// </summary>
+        public override string ToString()
+        {
+            return "Categorical(Dimension = " + _p.Length + ")";
+        }
+
+        /// <summary>
+        /// Checks whether the parameters of the distribution are valid. 
+        /// </summary>
+        /// <param name="p">An array of nonnegative ratios: this array does not need to be normalized 
+        /// as this is often impossible using floating point arithmetic.</param>
+        /// <returns>If any of the probabilities are negative returns false, or if the sum of parameters is 0.0; otherwise true</returns>
+        private static bool IsValidParameterSet(double[] p)
+        {
+            double sum = 0.0;
+            for (int i = 0; i < p.Length; i++)
+            {
+                if (p[i] < 0.0 || Double.IsNaN(p[i]))
+                {
+                    return false;
+                }
+                else
+                {
+                    sum += p[i];
+                }
+            }
+
+            if (sum == 0.0)
+            {
+                return false;
+            }
+
+            return true;
+        }
+
+        /// <summary>
+        /// Sets the parameters of the distribution after checking their validity.
+        /// </summary>
+        /// <param name="p">An array of nonnegative ratios: this array does not need to be normalized 
+        /// as this is often impossible using floating point arithmetic.</param>
+        /// <exception cref="ArgumentOutOfRangeException">When the parameters don't pass the <see cref="IsValidParameterSet"/> function.</exception>
+        private void SetParameters(double[] p)
+        {
+            if (Control.CheckDistributionParameters && !IsValidParameterSet(p))
+            {
+                throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters);
+            }
+
+            _p = (double[])p.Clone();
+        }
+
+        /// <summary>
+        /// Gets or sets the probability of generating a one.
+        /// </summary>
+        public double[] P
+        {
+            get
+            {
+                return (double[]) _p.Clone();
+            }
+
+            set
+            {
+                SetParameters(value);
+            }
+        }
+
+        #region IDistribution Members
+
+        /// <summary>
+        /// Gets or sets the random number generator which is used to draw random samples.
+        /// </summary>
+        public Random RandomSource
+        {
+            get
+            {
+                return _random;
+            }
+
+            set
+            {
+                if (value == null)
+                {
+                    throw new ArgumentNullException();
+                }
+
+                _random = value;
+            }
+        }
+
+        /// <summary>
+        /// Gets the mean of the distribution.
+        /// </summary>
+        public double Mean
+        {
+            get { return _p.Mean(); }
+        }
+
+        /// <summary>
+        /// Gets the standard deviation of the distribution.
+        /// </summary>
+        public double StdDev
+        {
+            get { return _p.StandardDeviation(); }
+        }
+
+        /// <summary>
+        /// Gets the variance of the distribution.
+        /// </summary>
+        public double Variance
+        {
+            get { return _p.Variance(); }
+        }
+
+        /// <summary>
+        /// Gets the entropy of the distribution.
+        /// </summary>
+        public double Entropy
+        {
+            get {
+                double E = 0.0;
+                for (int i = 0; i < _p.Length; i++)
+                {
+                    double p = _p[i];
+                    E += p * Math.Log(p);
+                }
+                return E;
+            }
+        }
+
+        /// <summary>
+        /// Gets the skewness of the distribution.
+        /// </summary>
+        public double Skewness
+        {
+            get { throw new NotImplementedException(); }
+        }
+
+        /// <summary>
+        /// Gets the smallest element in the domain of the distributions which can be represented by an integer.
+        /// </summary>
+        public int Minimum { get { return 0; } }
+
+        /// <summary>
+        /// Gets the largest element in the domain of the distributions which can be represented by an integer.
+        /// </summary>
+        public int Maximum { get { return _p.Length-1; } }
+
+        /// <summary>
+        /// Computes the cumulative distribution function of the Binomial distribution.
+        /// </summary>
+        /// <param name="x">The location at which to compute the cumulative density.</param>
+        /// <returns>the cumulative density at <paramref name="x"/>.</returns>
+        public double CumulativeDistribution(double x)
+        {
+            if (x < 0.0)
+            {
+                return 0.0;
+            }
+            else if (x >= _p.Length)
+            {
+                return 1.0;
+            }
+
+            var cdf = UnnormalizedCDF(_p);
+            return cdf[(int) Math.Floor(x)] / cdf[_p.Length - 1];
+        }
+
+        #endregion
+
+        #region IDiscreteDistribution Members
+
+        /// <summary>
+        /// The mode of the distribution.
+        /// </summary>
+        public int Mode
+        {
+            get { throw new NotImplementedException(); }
+        }
+
+        /// <summary>
+        /// The median of the distribution.
+        /// </summary>
+        public int Median
+        {
+            get { return (int) _p.Median(); }
+        }
+
+        /// <summary>
+        /// Computes the probability of a specific value.
+        /// </summary>
+        public double Probability(int val)
+        {
+            if (val < 0)
+            {
+                return 0.0;
+            }
+
+            if (val >= _p.Length)
+            {
+                return 0.0;
+            }
+
+            return _p[val];
+        }
+
+        /// <summary>
+        /// Computes the probability of a specific value.
+        /// </summary>
+        public double ProbabilityLn(int val)
+        {
+            if (val < 0)
+            {
+                return 0.0;
+            }
+
+            if (val >= _p.Length)
+            {
+                return 0.0;
+            }
+
+            return Math.Log(_p[val]);
+        }
+
+        /// <summary>
+        /// Samples a Binomially distributed random variable.
+        /// </summary>
+        /// <returns>The number of successful trials.</returns>
+        public int Sample()
+        {
+            return DoSample(RandomSource, _p);
+        }
+
+        /// <summary>
+        /// Samples an array of Bernoulli distributed random variables.
+        /// </summary>
+        /// <returns>a sequence of successful trial counts.</returns>
+        public IEnumerable<int> Samples()
+        {
+            while (true)
+            {
+                yield return DoSample(RandomSource, _p);
+            }
+        }
+
+        #endregion
+
+        /// <summary>
+        /// Samples one categorical distributed random variable; also known as the Discrete distribution.
+        /// </summary>
+        /// <param name="rnd">The random number generator to use.</param>
+        /// <param name="p">An array of nonnegative ratios: this array does not need to be normalized 
+        /// as this is often impossible using floating point arithmetic.</param>
+        /// <returns>One random integer between 0 and the size of the categorical (exclusive).</returns>
+        public static int Sample(System.Random rnd, double[] p)
+        {
+            if (Control.CheckDistributionParameters && !IsValidParameterSet(p))
+            {
+                throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters);
+            }
+
+            // The cumulative density of p.
+            double[] cp = UnnormalizedCDF(p);
+
+            return DoSample(rnd, cp);
+        }
+
+        /// <summary>
+        /// Samples a categorically distributed random variable.
+        /// </summary>
+        /// <param name="rnd">The random number generator to use.</param>
+        /// <param name="p">An array of nonnegative ratios: this array does not need to be normalized 
+        /// as this is often impossible using floating point arithmetic.</param>
+        /// <returns><paramref name="n"/> random integers between 0 and the size of the categorical (exclusive).</returns>
+        public static IEnumerable<int> Samples(System.Random rnd, double[] p)
+        {
+            if (Control.CheckDistributionParameters && !IsValidParameterSet(p))
+            {
+                throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters);
+            }
+
+            // The cumulative density of p.
+            double[] cp = UnnormalizedCDF(p);
+
+            while (true)
+            {
+                yield return DoSample(rnd, cp);
+            }
+        }
+
+        /// <summary>
+        /// Computes the unnormalized cumulative distribution function. This method performs no
+        /// parameter checking.
+        /// </summary>
+        /// <param name="p">An array of nonnegative ratios: this array does not need to be normalized 
+        /// as this is often impossible using floating point arithmetic.</param>
+        /// <returns>An array representing the unnormalized cumulative distribution function.</returns>
+        internal static double[] UnnormalizedCDF(double[] p)
+        {
+            double[] cp = (double[]) p.Clone();
+
+            for (int i = 1; i < p.Length; i++)
+            {
+                cp[i] += cp[i - 1];
+            }
+
+            return cp;
+        }
+
+        /// <summary>
+        /// Returns one trials from the categorical distribution.
+        /// </summary>
+        /// <param name="rnd">The random number generator to use.</param>
+        /// <param name="cdf">The cumulative distribution of the probability distribution.</param>
+        /// <returns>One sample from the categorical distribution implied by <see cref="cdf"/>.</returns>
+        internal static int DoSample(System.Random rnd, double[] cdf)
+        {
+            // TODO : use binary search to speed up this procedure.
+            double u = rnd.NextDouble() * cdf[cdf.Length - 1];
+            int idx = 0;
+            while (u > cdf[idx])
+            {
+                idx++;
+            }
+            return idx;
+        }
+    }
+}

src/Numerics/Distributions/Multivariate/Multinomial.cs

@@ -1,4 +1,4 @@
-// <copyright file="Bernoulli.cs" company="Math.NET">
+// <copyright file="Multinomial.cs" company="Math.NET">
 // Math.NET Numerics, part of the Math.NET Project
 // http://mathnet.opensourcedotnet.info
 //
@@ -52,6 +52,11 @@ namespace MathNet.Numerics.Distributions
         /// </summary>
         private double[] _p;
 
+        /// <summary>
+        /// The number of trials.
+        /// </summary>
+        private int _n;
+
         /// <summary>
         /// The distribution's random number generator.
         /// </summary>
@@ -62,10 +67,12 @@ namespace MathNet.Numerics.Distributions
         /// </summary>
         /// <param name="p">An array of nonnegative ratios: this array does not need to be normalized 
         /// as this is often impossible using floating point arithmetic.</param>
-        /// <exception cref="ArgumentException">If any of the probabilities are negative or do not sum to one.</exception>
-        public Multinomial(double[] p)
+        /// <param name="n">The number of trials.</param>
+        /// <exception cref="ArgumentOutOfRangeException">If any of the probabilities are negative or do not sum to one.</exception>
+        /// <exception cref="ArgumentOutOfRangeException">If <paramref name="n"/> is negative.</exception>
+        public Multinomial(double[] p, int n)
         {
-            SetParameters(p);
+            SetParameters(p, n);
             RandomSource = new System.Random();
         }
 
@@ -93,7 +100,7 @@ namespace MathNet.Numerics.Distributions
         /// </summary>
         public override string ToString()
         {
-            return "Multinomial(Dimension = " + _p.Length + ")";
+            return "Multinomial(Dimension = " + _p.Length + ", Number of Trails = " + _n + ")";
         }
 
         /// <summary>
@@ -101,8 +108,10 @@ namespace MathNet.Numerics.Distributions
         /// </summary>
         /// <param name="p">An array of nonnegative ratios: this array does not need to be normalized 
         /// as this is often impossible using floating point arithmetic.</param>
-        /// <returns>If any of the probabilities are negative returns false, or if the sum of parameters is 0.0; otherwise true</returns>
-        private static bool IsValidParameterSet(double[] p)
+        /// <param name="n">The number of trials.</param>
+        /// <returns>If any of the probabilities are negative returns false, 
+        /// if the sum of parameters is 0.0, or if the number of trials is negative; otherwise true</returns>
+        private static bool IsValidParameterSet(double[] p, int n)
         {
             double sum = 0.0;
             for (int i = 0; i < p.Length; i++)
@@ -122,6 +131,11 @@ namespace MathNet.Numerics.Distributions
                 return false;
             }
 
+            if (n < 0)
+            {
+                return false;
+            }
+
             return true;
         }
 
@@ -130,19 +144,21 @@ namespace MathNet.Numerics.Distributions
         /// </summary>
         /// <param name="p">An array of nonnegative ratios: this array does not need to be normalized 
         /// as this is often impossible using floating point arithmetic.</param>
+        /// <param name="n">The number of trials.</param>
         /// <exception cref="ArgumentOutOfRangeException">When the parameters don't pass the <see cref="IsValidParameterSet"/> function.</exception>
-        private void SetParameters(double[] p)
+        private void SetParameters(double[] p, int n)
         {
-            if (Control.CheckDistributionParameters && !IsValidParameterSet(p))
+            if (Control.CheckDistributionParameters && !IsValidParameterSet(p, n))
             {
                 throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters);
             }
 
             _p = (double[])p.Clone();
+            _n = n;
         }
 
         /// <summary>
-        /// Gets or sets the probability of generating a one.
+        /// Gets or sets the proportion of ratios.
         /// </summary>
         public double[] P
         {
@@ -153,7 +169,23 @@ namespace MathNet.Numerics.Distributions
 
             set
             {
-                SetParameters(value);
+                SetParameters(value, _n);
+            }
+        }
+
+        /// <summary>
+        /// Gets or sets the number of trials.
+        /// </summary>
+        public int N
+        {
+            get
+            {
+                return _n;
+            }
+
+            set
+            {
+                SetParameters(_p, value);
             }
         }
 
@@ -179,100 +211,84 @@ namespace MathNet.Numerics.Distributions
         }
 
         /// <summary>
-        /// Samples one multinomial distributed random variable; also known as the Discrete distribution.
+        /// Samples one multinomial distributed random variable.
         /// </summary>
-        /// <returns>One random integer between 0 and the size of the multinomial (exclusive).</returns>
-        public int Sample()
+        /// <returns>the counts for each of the different possible values.</returns>
+        public int[] Sample()
         {
-            return Sample(RandomSource, _p);
+            return Sample(RandomSource, _p, _n);
         }
 
         /// <summary>
-        /// Samples a multinomially distributed random variable.
+        /// Samples a sequence multinomially distributed random variables.
         /// </summary>
-        /// <param name="n">The number of variables needed.</param>
-        /// <returns><paramref name="n"/> random integers between 0 and the size of the multinomial (exclusive).</returns>
-        public int[] Sample(int n)
+        /// <returns>a sequence of counts for each of the different possible values.</returns>
+        public IEnumerable<int[]> Samples()
         {
-            return Sample(RandomSource, n, _p);
+            while (true)
+            {
+                yield return Sample(RandomSource, _p, _n);
+            }
         }
 
         /// <summary>
-        /// Samples one multinomial distributed random variable; also known as the Discrete distribution.
+        /// Samples one multinomial distributed random variable.
         /// </summary>
         /// <param name="rnd">The random number generator to use.</param>
         /// <param name="p">An array of nonnegative ratios: this array does not need to be normalized 
         /// as this is often impossible using floating point arithmetic.</param>
-        /// <returns>One random integer between 0 and the size of the multinomial (exclusive).</returns>
-        public static int Sample(System.Random rnd, double[] p)
+        /// <param name="n">The number of trials.</param>
+        /// <returns>the counts for each of the different possible values.</returns>
+        public static int[] Sample(System.Random rnd, double[] p, int n)
         {
-            if (Control.CheckDistributionParameters && !IsValidParameterSet(p))
+            if (Control.CheckDistributionParameters && !IsValidParameterSet(p, n))
             {
                 throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters);
             }
 
             // The cumulative density of p.
-            double[] cp = UnnormalizedCDF(p);
+            double[] cp = Categorical.UnnormalizedCDF(p);
+            // The variable that stores the counts.
+            int[] ret = new int[p.Length];
 
-            double u = rnd.NextDouble()*cp[cp.Length - 1];
-            int idx = 0;
-            while (u > cp[idx])
+            for (int i = 0; i < n; i++)
             {
-                idx++;
+                ret[Categorical.DoSample(rnd, cp)]++;
             }
-            return idx;
+
+            return ret;
         }
 
         /// <summary>
         /// Samples a multinomially distributed random variable.
         /// </summary>
         /// <param name="rnd">The random number generator to use.</param>
-        /// <param name="n">The number of variables needed.</param>
         /// <param name="p">An array of nonnegative ratios: this array does not need to be normalized 
         /// as this is often impossible using floating point arithmetic.</param>
-        /// <returns><paramref name="n"/> random integers between 0 and the size of the multinomial (exclusive).</returns>
-        public static int[] Sample(System.Random rnd, int n, double[] p)
+        /// <param name="n">The number of variables needed.</param>
+        /// <returns>a sequence of counts for each of the different possible values.</returns>
+        public static IEnumerable<int[]> Samples(System.Random rnd, double[] p, int n)
         {
-            if (Control.CheckDistributionParameters && !IsValidParameterSet(p))
+            if (Control.CheckDistributionParameters && !IsValidParameterSet(p, n))
             {
                 throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters);
             }
 
             // The cumulative density of p.
-            double[] cp = UnnormalizedCDF(p);
+            double[] cp = Categorical.UnnormalizedCDF(p);
 
-            int[] arr = new int[n];
-            for (int i = 0; i < n; i++)
+            while (true)
             {
-                double u = rnd.NextDouble()*cp[cp.Length - 1];
-                int idx = 0;
-                while (u > cp[idx])
+                // The variable that stores the counts.
+                int[] ret = new int[p.Length];
+
+                for (int i = 0; i < n; i++)
                 {
-                    idx++;
+                    ret[Categorical.DoSample(rnd, cp)]++;
                 }
-                arr[i] = idx;
-            }
 
-            return arr;
-        }
-
-        /// <summary>
-        /// Computes the unnormalized cumulative distribution function. This method performs no
-        /// parameter checking.
-        /// </summary>
-        /// <param name="p">An array of nonnegative ratios: this array does not need to be normalized 
-        /// as this is often impossible using floating point arithmetic.</param>
-        /// <returns>An array representing the unnormalized cumulative distribution function.</returns>
-        private static double[] UnnormalizedCDF(double[] p)
-        {
-            double[] cp = (double[]) p.Clone();
-
-            for (int i = 1; i < p.Length; i++)
-            {
-                cp[i] += cp[i - 1];
+                yield return ret;
             }
-
-            return cp;
         }
     }
 }

src/Numerics/Numerics.csproj

@@ -79,6 +79,8 @@
     <Compile Include="Distributions\Continuous\Gamma.cs" />
     <Compile Include="Distributions\Continuous\Normal.cs" />
     <Compile Include="Distributions\Discrete\Bernoulli.cs" />
+    <Compile Include="Distributions\Discrete\Binomial.cs" />
+    <Compile Include="Distributions\Discrete\Categorical.cs" />
     <Compile Include="Distributions\Discrete\DiscreteUniform.cs" />
     <Compile Include="Distributions\IContinuousDistribution.cs" />
     <Compile Include="Distributions\IDiscreteDistribution.cs" />

src/UnitTests/DistributionTests/CommonDistributionTests.cs

@@ -41,7 +41,7 @@ namespace MathNet.Numerics.UnitTests.DistributionTests
         [SetUp]
         public void SetupDistributions()
         {
-            dists = new IDistribution[8];
+            dists = new IDistribution[10];
 
             dists[0] = new Beta(1.0, 1.0);
             dists[1] = new ContinuousUniform(0.0, 1.0);
@@ -51,6 +51,8 @@ namespace MathNet.Numerics.UnitTests.DistributionTests
             dists[5] = new Weibull(1.0, 1.0);
             dists[6] = new DiscreteUniform(1, 10);
             dists[7] = new LogNormal(1.0, 1.0);
+            dists[8] = new Binomial(0.7, 10);
+            dists[9] = new Categorical(0.7);
         }
 
         [Test]

src/UnitTests/DistributionTests/Discrete/BinomialTests.cs

@@ -0,0 +1,248 @@
+// <copyright file="BinomialTests.cs" company="Math.NET">
+// Math.NET Numerics, part of the Math.NET Project
+// http://mathnet.opensourcedotnet.info
+//
+// Copyright (c) 2009 Math.NET
+//
+// Permission is hereby granted, free of charge, to any person
+// obtaining a copy of this software and associated documentation
+// files (the "Software"), to deal in the Software without
+// restriction, including without limitation the rights to use,
+// copy, modify, merge, publish, distribute, sublicense, and/or sell
+// copies of the Software, and to permit persons to whom the
+// Software is furnished to do so, subject to the following
+// conditions:
+//
+// The above copyright notice and this permission notice shall be
+// included in all copies or substantial portions of the Software.
+//
+// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+// OTHER DEALINGS IN THE SOFTWARE.
+// </copyright>
+
+namespace MathNet.Numerics.UnitTests.DistributionTests
+{
+    using System;
+    using System.Linq;
+    using MbUnit.Framework;
+    using MathNet.Numerics.Distributions;
+
+    [TestFixture]
+    public class BinomialTests
+    {
+        [SetUp]
+        public void SetUp()
+        {
+            Control.CheckDistributionParameters = true;
+        }
+
+        [Test]
+        [Row(0.0, 4)]
+        [Row(0.3, 3)]
+        [Row(1.0, 2)]
+        public void CanCreateBinomial(double p, int n)
+        {
+            var bernoulli = new Binomial(p,n);
+            AssertEx.AreEqual<double>(p, bernoulli.P);
+        }
+
+        [Test]
+        [ExpectedException(typeof(ArgumentOutOfRangeException))]
+        [Row(Double.NaN, 1)]
+        [Row(-1.0, 1)]
+        [Row(2.0, 1)]
+        [Row(0.3, -2)]
+        public void BinomialCreateFailsWithBadParameters(double p, int n)
+        {
+            var bernoulli = new Binomial(p,n);
+        }
+
+        [Test]
+        public void ValidateToString()
+        {
+            var b = new Binomial(0.3, 2);
+            AssertEx.AreEqual<string>("Binomial(Success Probability = 0.3, Number of Trials = 2)", b.ToString());
+        }
+
+        [Test]
+        [Row(0.0, 4)]
+        [Row(0.3, 3)]
+        [Row(1.0, 2)]
+        public void CanSetSuccessProbability(double p, int n)
+        {
+            var b = new Binomial(0.3, n);
+            b.P = p;
+        }
+
+        [Test]
+        [ExpectedException(typeof(ArgumentOutOfRangeException))]
+        [Row(Double.NaN, 1)]
+        [Row(-1.0, 1)]
+        [Row(2.0, 1)]
+        public void SetProbabilityOfOneFails(double p, int n)
+        {
+            var b = new Binomial(0.3, n);
+            b.P = p;
+        }
+
+        [Test]
+        [Row(0.0, 4)]
+        [Row(0.3, 3)]
+        [Row(1.0, 2)]
+        public void ValidateEntropy(double p, int n)
+        {
+            var b = new Binomial(p,n);
+            AssertHelpers.AlmostEqual(n * (-(1.0 - p) * Math.Log(1.0 - p) - p * Math.Log(p)), b.Entropy, 14);
+        }
+
+        [Test]
+        [Row(0.0, 4)]
+        [Row(0.3, 3)]
+        [Row(1.0, 2)]
+        public void ValidateSkewness(double p, int n)
+        {
+            var b = new Binomial(p,n);
+            AssertEx.AreEqual<double>((1.0 - 2.0 * p) / Math.Sqrt(n * p * (1.0 - p)), b.Skewness);
+        }
+
+        [Test]
+        [Row(0.0, 4, 0.0)]
+        [Row(0.3, 3, 1.0)]
+        [Row(1.0, 2, 1.0)]
+        public void ValidateMode(double p, int n, double m)
+        {
+            var b = new Binomial(p,n);
+            AssertEx.AreEqual<double>(m, b.Mode);
+        }
+
+        [Test]
+        public void ValidateMinimum()
+        {
+            var b = new Binomial(0.3, 10);
+            AssertEx.AreEqual<int>(0, b.Minimum);
+        }
+
+        [Test]
+        public void ValidateMaximum()
+        {
+            var b = new Binomial(0.3, 10);
+            AssertEx.AreEqual<int>(10, b.Maximum);
+        }
+
+        [Test]
+        [Row(0.000000, 1, 0, 1.0)]
+        [Row(0.000000, 1, 1, 0.0)]
+        [Row(0.000000, 1, 1, 0.0)]
+        [Row(0.000000, 3, 0, 1.0)]
+        [Row(0.000000, 3, 1, 0.0)]
+        [Row(0.000000, 3, 3, 0.0)]
+        [Row(0.000000, 10, 0, 1.0)]
+        [Row(0.000000, 10, 1, 0.0)]
+        [Row(0.000000, 10, 10, 0.0)]
+        [Row(0.300000, 1, 0, 0.69999999999999995559107901499373838305473327636719)]
+        [Row(0.300000, 1, 1, 0.2999999999999999888977697537484345957636833190918)]
+        [Row(0.300000, 1, 1, 0.2999999999999999888977697537484345957636833190918)]
+        [Row(0.300000, 3, 0, 0.34299999999999993471888615204079956461021032657166)]
+        [Row(0.300000, 3, 1, 0.44099999999999992772448109690231306411849135972008)]
+        [Row(0.300000, 3, 3, 0.026999999999999997002397833512077451789759292859569)]
+        [Row(0.300000, 10, 0, 0.02824752489999998207939855277004937778546385011091)]
+        [Row(0.300000, 10, 1, 0.12106082099999992639752977030555903089040470780077)]
+        [Row(0.300000, 10, 10, 0.0000059048999999999978147480206303047454017251032868501)]
+        [Row(1.000000, 1, 0, 0.0)]
+        [Row(1.000000, 1, 1, 1.0)]
+        [Row(1.000000, 1, 1, 1.0)]
+        [Row(1.000000, 3, 0, 0.0)]
+        [Row(1.000000, 3, 1, 0.0)]
+        [Row(1.000000, 3, 3, 1.0)]
+        [Row(1.000000, 10, 0, 0.0)]
+        [Row(1.000000, 10, 1, 0.0)]
+        [Row(1.000000, 10, 10, 1.0)]
+        public void ValidateProbability(double p, int n, int x, double d)
+        {
+            var b = new Binomial(p,n);
+            AssertEx.AreEqual(d, b.Probability(x));
+        }
+
+        [Test]
+        [Row(0.000000, 1, 0, 0.0)]
+        [Row(0.000000, 1, 1, -inf)]
+        [Row(0.000000, 1, 1, -inf)]
+        [Row(0.000000, 3, 0, 0.0)]
+        [Row(0.000000, 3, 1, -inf)]
+        [Row(0.000000, 3, 3, -inf)]
+        [Row(0.000000, 10, 0, 0.0)]
+        [Row(0.000000, 10, 1, -inf)]
+        [Row(0.000000, 10, 10, -inf)]
+        [Row(0.300000, 1, 0, -0.3566749439387324423539544041072745145718090708995)]
+        [Row(0.300000, 1, 1, -1.2039728043259360296301803719337238685164245381839)]
+        [Row(0.300000, 1, 1, -1.2039728043259360296301803719337238685164245381839)]
+        [Row(0.300000, 3, 0, -1.0700248318161973270618632123218235437154272126985)]
+        [Row(0.300000, 3, 1, -0.81871040353529122294284394322574719301255212216016)]
+        [Row(0.300000, 3, 3, -3.6119184129778080888905411158011716055492736145517)]
+        [Row(0.300000, 10, 0, -3.566749439387324423539544041072745145718090708995)]
+        [Row(0.300000, 10, 1, -2.1114622067804823267977785542148302920616046876506)]
+        [Row(0.300000, 10, 10, -12.039728043259360296301803719337238685164245381839)]
+        [Row(1.000000, 1, 0, -inf)]
+        [Row(1.000000, 1, 1, 0.0)]
+        [Row(1.000000, 1, 1, 0.0)]
+        [Row(1.000000, 3, 0, -inf)]
+        [Row(1.000000, 3, 1, -inf)]
+        [Row(1.000000, 3, 3, 0.0)]
+        [Row(1.000000, 10, 0, -inf)]
+        [Row(1.000000, 10, 1, -inf)]
+        [Row(1.000000, 10, 10, 0.0)]
+        public void ValidateProbabilityLn(double p, int n, int x, double dln)
+        {
+            var b = new Binomial(p,n);
+            AssertEx.AreEqual(dln, b.ProbabilityLn(x));
+        }
+
+        [Test]
+        public void CanSampleStatic()
+        {
+            var d = Binomial.Sample(new Random(), 0.3, 5);
+        }
+
+        [Test]
+        public void CanSampleSequenceStatic()
+        {
+            var ied = Binomial.Samples(new Random(), 0.3, 5);
+            var arr = ied.Take(5).ToArray();
+        }
+
+        [Test]
+        [ExpectedException(typeof(ArgumentOutOfRangeException))]
+        public void FailSampleStatic()
+        {
+            var d = Binomial.Sample(new Random(), -1.0, 5);
+        }
+
+        [Test]
+        [ExpectedException(typeof(ArgumentOutOfRangeException))]
+        public void FailSampleSequenceStatic()
+        {
+            var ied = Binomial.Samples(new Random(), -1.0, 5).First();
+        }
+
+        [Test]
+        public void CanSample()
+        {
+            var n = new Binomial(0.3, 5);
+            var d = n.Sample();
+        }
+
+        [Test]
+        public void CanSampleSequence()
+        {
+            var n = new Binomial(0.3, 5);
+            var ied = n.Samples();
+            var e = ied.Take(5).ToArray();
+        }
+    }
+}

src/UnitTests/DistributionTests/Discrete/CategoricalTests.cs

@@ -0,0 +1,117 @@
+// <copyright file="CategorialTests.cs" company="Math.NET">
+// Math.NET Numerics, part of the Math.NET Project
+// http://mathnet.opensourcedotnet.info
+//
+// Copyright (c) 2009 Math.NET
+//
+// Permission is hereby granted, free of charge, to any person
+// obtaining a copy of this software and associated documentation
+// files (the "Software"), to deal in the Software without
+// restriction, including without limitation the rights to use,
+// copy, modify, merge, publish, distribute, sublicense, and/or sell
+// copies of the Software, and to permit persons to whom the
+// Software is furnished to do so, subject to the following
+// conditions:
+//
+// The above copyright notice and this permission notice shall be
+// included in all copies or substantial portions of the Software.
+//
+// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+// OTHER DEALINGS IN THE SOFTWARE.
+// </copyright>
+
+namespace MathNet.Numerics.UnitTests.DistributionTests
+{
+    using System;
+    using System.Linq;
+    using MbUnit.Framework;
+    using MathNet.Numerics.Distributions;
+
+    [TestFixture]
+    public class CategoricalTests
+    {
+        double[] badP;
+        double[] badP2;
+        double[] smallP;
+        double[] largeP;
+
+        [SetUp]
+        public void SetUp()
+        {
+            Control.CheckDistributionParameters = true;
+            badP = new double[] { -1.0, 1.0 };
+            badP2 = new double[] { 0.0, 0.0 };
+            smallP = new double[] { 1.0, 1.0, 1.0 };
+            largeP = new double[] { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0 };
+        }
+
+        [Test]
+        public void CanCreateCategorical()
+        {
+            var m = new Categorical(largeP, 4);
+            AssertEx.AreEqual<double[]>(largeP, m.P);
+        }
+
+        [Test]
+        [ExpectedException(typeof(ArgumentOutOfRangeException))]
+        public void CategoricalCreateFailsWithNegativeRatios()
+        {
+            var m = new Categorical(badP, 4);
+        }
+
+        [Test]
+        [ExpectedException(typeof(ArgumentOutOfRangeException))]
+        public void CategoricalCreateFailsWithAllZeroRatios()
+        {
+            var m = new Categorical(badP2, 4);
+        }
+
+        [Test]
+        public void ValidateToString()
+        {
+            var b = new Categorical(smallP);
+            AssertEx.AreEqual<string>("Categorical(Dimension = 3)", b.ToString());
+        }
+
+        [Test]
+        public void CanSetProbability()
+        {
+            var b = new Categorical(largeP, 4);
+            b.P = smallP;
+        }
+
+        [Test]
+        [ExpectedException(typeof(ArgumentOutOfRangeException))]
+        public void SetProbabilityFails()
+        {
+            var b = new Categorical(largeP, 4);
+            b.P = badP;
+        }
+
+        [Test]
+        public void CanSampleStatic()
+        {
+            var d = Categorical.Sample(new Random(), largeP, 4);
+        }
+
+        [Test]
+        [ExpectedException(typeof(ArgumentOutOfRangeException))]
+        public void FailSampleStatic()
+        {
+            var d = Categorical.Sample(new Random(), badP, 4);
+        }
+
+        [Test]
+        public void CanSample()
+        {
+            var n = new Categorical(largeP, 4);
+            var d = n.Sample();
+        }
+    }
+}

src/UnitTests/DistributionTests/Multivariate/MultinomialTests.cs

@@ -54,7 +54,7 @@ namespace MathNet.Numerics.UnitTests.DistributionTests
         [Test]
         public void CanCreateMultinomial()
         {
-            var m = new Multinomial(largeP);
+            var m = new Multinomial(largeP, 4);
             AssertEx.AreEqual<double[]>(largeP, m.P);
         }
 
@@ -62,27 +62,27 @@ namespace MathNet.Numerics.UnitTests.DistributionTests
         [ExpectedException(typeof(ArgumentOutOfRangeException))]
         public void MultinomialCreateFailsWithNegativeRatios()
         {
-            var m = new Multinomial(badP);
+            var m = new Multinomial(badP, 4);
         }
 
         [Test]
         [ExpectedException(typeof(ArgumentOutOfRangeException))]
         public void MultinomialCreateFailsWithAllZeroRatios()
         {
-            var m = new Multinomial(badP2);
+            var m = new Multinomial(badP2, 4);
         }
 
         [Test]
         public void ValidateToString()
         {
-            var b = new Multinomial(smallP);
+            var b = new Multinomial(smallP, 4);
             AssertEx.AreEqual<string>("Multinomial(Dimension = 3)", b.ToString());
         }
 
         [Test]
         public void CanSetProbability()
         {
-            var b = new Multinomial(largeP);
+            var b = new Multinomial(largeP, 4);
             b.P = smallP;
         }
 
@@ -90,27 +90,27 @@ namespace MathNet.Numerics.UnitTests.DistributionTests
         [ExpectedException(typeof(ArgumentOutOfRangeException))]
         public void SetProbabilityFails()
         {
-            var b = new Multinomial(largeP);
+            var b = new Multinomial(largeP, 4);
             b.P = badP;
         }
 
         [Test]
         public void CanSampleStatic()
         {
-            var d = Multinomial.Sample(new Random(), largeP);
+            var d = Multinomial.Sample(new Random(), largeP, 4);
         }
 
         [Test]
         [ExpectedException(typeof(ArgumentOutOfRangeException))]
         public void FailSampleStatic()
         {
-            var d = Multinomial.Sample(new Random(), badP);
+            var d = Multinomial.Sample(new Random(), badP, 4);
         }
 
         [Test]
         public void CanSample()
         {
-            var n = new Multinomial(largeP);
+            var n = new Multinomial(largeP, 4);
             var d = n.Sample();
         }
     }

src/UnitTests/UnitTests.csproj

@@ -72,6 +72,8 @@
     <Compile Include="DistributionTests\Continuous\GammaTests.cs" />
     <Compile Include="DistributionTests\Continuous\NormalTests.cs" />
     <Compile Include="DistributionTests\Discrete\BernoulliTests.cs" />
+    <Compile Include="DistributionTests\Discrete\BinomialTests.cs" />
+    <Compile Include="DistributionTests\Discrete\CategoricalTests.cs" />
     <Compile Include="DistributionTests\Discrete\DiscreteUniformTests.cs" />
     <Compile Include="DistributionTests\Multivariate\DirichletTests.cs" />
     <Compile Include="DistributionTests\Multivariate\MultinomialTests.cs" />