Exemple #1
0
        public void ValidateDensityLn(double scale, double x)
        {
            var    n        = new Rayleigh(scale);
            double expected = Math.Log(x / (scale * scale)) - (x * (x / (2.0 * (scale * scale))));

            Assert.AreEqual(expected, n.DensityLn(x));
            Assert.AreEqual(expected, Rayleigh.PDFLn(scale, x));
        }
        /// <summary>
        /// Run example
        /// </summary>
        /// <a href="http://en.wikipedia.org/wiki/Rayleigh_distribution">Rayleigh distribution</a>
        public void Run()
        {
            // 1. Initialize the new instance of the Rayleigh distribution class with parameter Scale = 1.
            var rayleigh = new Rayleigh(1);

            Console.WriteLine(@"1. Initialize the new instance of the Rayleigh distribution class with parameter Scale = {0}", rayleigh.Scale);
            Console.WriteLine();

            // 2. Distributuion properties:
            Console.WriteLine(@"2. {0} distributuion properties:", rayleigh);

            // Cumulative distribution function
            Console.WriteLine(@"{0} - Сumulative distribution at location '0.3'", rayleigh.CumulativeDistribution(0.3).ToString(" #0.00000;-#0.00000"));

            // Probability density
            Console.WriteLine(@"{0} - Probability density at location '0.3'", rayleigh.Density(0.3).ToString(" #0.00000;-#0.00000"));

            // Log probability density
            Console.WriteLine(@"{0} - Log probability density at location '0.3'", rayleigh.DensityLn(0.3).ToString(" #0.00000;-#0.00000"));

            // Entropy
            Console.WriteLine(@"{0} - Entropy", rayleigh.Entropy.ToString(" #0.00000;-#0.00000"));

            // Largest element in the domain
            Console.WriteLine(@"{0} - Largest element in the domain", rayleigh.Maximum.ToString(" #0.00000;-#0.00000"));

            // Smallest element in the domain
            Console.WriteLine(@"{0} - Smallest element in the domain", rayleigh.Minimum.ToString(" #0.00000;-#0.00000"));

            // Mean
            Console.WriteLine(@"{0} - Mean", rayleigh.Mean.ToString(" #0.00000;-#0.00000"));

            // Median
            Console.WriteLine(@"{0} - Median", rayleigh.Median.ToString(" #0.00000;-#0.00000"));

            // Mode
            Console.WriteLine(@"{0} - Mode", rayleigh.Mode.ToString(" #0.00000;-#0.00000"));

            // Variance
            Console.WriteLine(@"{0} - Variance", rayleigh.Variance.ToString(" #0.00000;-#0.00000"));

            // Standard deviation
            Console.WriteLine(@"{0} - Standard deviation", rayleigh.StdDev.ToString(" #0.00000;-#0.00000"));

            // Skewness
            Console.WriteLine(@"{0} - Skewness", rayleigh.Skewness.ToString(" #0.00000;-#0.00000"));
            Console.WriteLine();

            // 3. Generate 10 samples of the Rayleigh distribution
            Console.WriteLine(@"3. Generate 10 samples of the Rayleigh distribution");
            for (var i = 0; i < 10; i++)
            {
                Console.Write(rayleigh.Sample().ToString("N05") + @" ");
            }

            Console.WriteLine();
            Console.WriteLine();

            // 4. Generate 100000 samples of the Rayleigh(1) distribution and display histogram
            Console.WriteLine(@"4. Generate 100000 samples of the Rayleigh(1) distribution and display histogram");
            var data = new double[100000];

            for (var i = 0; i < data.Length; i++)
            {
                data[i] = rayleigh.Sample();
            }

            ConsoleHelper.DisplayHistogram(data);
            Console.WriteLine();

            // 5. Generate 100000 samples of the Rayleigh(4) distribution and display histogram
            Console.WriteLine(@"5. Generate 100000 samples of the Rayleigh(4) distribution and display histogram");
            rayleigh.Scale = 4;
            for (var i = 0; i < data.Length; i++)
            {
                data[i] = rayleigh.Sample();
            }

            ConsoleHelper.DisplayHistogram(data);
            Console.WriteLine();

            // 6. Generate 100000 samples of the Rayleigh(0.5) distribution and display histogram
            Console.WriteLine(@"6. Generate 100000 samples of the Rayleigh(0.5) distribution and display histogram");
            rayleigh.Scale = 0.5;
            for (var i = 0; i < data.Length; i++)
            {
                data[i] = rayleigh.Sample();
            }

            ConsoleHelper.DisplayHistogram(data);
        }
 public void ValidateDensityLn([Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double scale, [Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double x)
 {
     var n = new Rayleigh(scale);
     Assert.AreEqual(Math.Log(x / (scale * scale)) - (x * (x / (2.0 * (scale * scale)))), n.DensityLn(x));
 }
Exemple #4
0
        public void ValidateDensityLn(double scale, double x)
        {
            var n = new Rayleigh(scale);

            Assert.AreEqual(Math.Log(x / (scale * scale)) - (x * (x / (2.0 * (scale * scale)))), n.DensityLn(x));
        }
 public void ValidateDensityLn(double scale, double x)
 {
     var n = new Rayleigh(scale);
     Assert.AreEqual<double>(Math.Log(x / (scale * scale)) - x * x / (2.0 * scale * scale), n.DensityLn(x));
 }
Exemple #6
0
        public void ValidateDensityLn([Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double scale, [Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double x)
        {
            var n = new Rayleigh(scale);

            Assert.AreEqual(Math.Log(x / (scale * scale)) - (x * (x / (2.0 * (scale * scale)))), n.DensityLn(x));
        }