Accord.Statistics.Distributions.Multivariate.InverseWishartDistribution.ProbabilityDensityFunction C# (CSharp) Method

        public override double ProbabilityDensityFunction(params double[] x)
        {
            double[,] X = x.Reshape(size, size);
            return ProbabilityDensityFunction(X);
        }

        public void ConstructorTest4()
        {
            // Create a Inverse Wishart with the parameters
            var invWishart = new InverseWishartDistribution(

                // Degrees of freedom
                degreesOfFreedom: 4,

                // Scale parameter
                inverseScale: new double[,] 
                {
                     {  1.7, -0.2 },
                     { -0.2,  5.3 },
                }
            );

            // Common measures
            double[] var = invWishart.Variance;  // { -3.4, -10.6 }
            double[,] cov = invWishart.Covariance;  // see below
            double[,] mmean = invWishart.MeanMatrix; // see below
            
            //        cov                mean
            //   -5.78   -4.56        1.7  -0.2 
            //   -4.56  -56.18       -0.2   5.3 

            // (the above matrix representations have been transcribed to text using)
            string scov = cov.ToString(DefaultMatrixFormatProvider.InvariantCulture);
            string smean = mmean.ToString(DefaultMatrixFormatProvider.InvariantCulture);

            // For compatibility reasons, .Mean stores a flattened mean matrix
            double[] mean = invWishart.Mean; // { 1.7, -0.2, -0.2, 5.3 }


            // Probability density functions
            double pdf = invWishart.ProbabilityDensityFunction(new double[,] 
            {
                {  5.2,  0.2 }, // 0.000029806281690351203
                {  0.2,  4.2 },
            });

            double lpdf = invWishart.LogProbabilityDensityFunction(new double[,] 
            {
                {  5.2,  0.2 }, // -10.420791391688828
                {  0.2,  4.2 },
            });


            Assert.AreEqual(pdf, System.Math.Exp(lpdf), 1e-6);
            Assert.AreEqual(1.7, mean[0]);
            Assert.AreEqual(-0.2, mean[1]);
            Assert.AreEqual(-0.2, mean[2]);
            Assert.AreEqual(5.3, mean[3]);
            Assert.AreEqual(-3.4, var[0]);
            Assert.AreEqual(-10.6, var[1]);
            Assert.AreEqual(-5.7799999999999994, cov[0, 0]);
            Assert.AreEqual(-4.5649999999999995, cov[0, 1]);
            Assert.AreEqual(-4.5649999999999995, cov[1, 0]);
            Assert.AreEqual(-56.18, cov[1, 1]);
            Assert.AreEqual(0.000029806281690351203, pdf);
            Assert.AreEqual(-10.420791391688828, lpdf);
        }