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C# StudentT.DensityLn方法代码示例

本文整理汇总了C#中MathNet.Numerics.Distributions.StudentT.DensityLn方法的典型用法代码示例。如果您正苦于以下问题:C# StudentT.DensityLn方法的具体用法?C# StudentT.DensityLn怎么用?C# StudentT.DensityLn使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在MathNet.Numerics.Distributions.StudentT的用法示例。


在下文中一共展示了StudentT.DensityLn方法的2个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的C#代码示例。

示例1: Run

        /// <summary>
        /// Run example
        /// </summary>
        /// <a href="http://en.wikipedia.org/wiki/StudentT_distribution">StudentT distribution</a>
        public void Run()
        {
            // 1. Initialize the new instance of the StudentT distribution class with parameters Location = 0, Scale = 1, DegreesOfFreedom = 1
            var studentT = new StudentT();
            Console.WriteLine(@"1. Initialize the new instance of the StudentT distribution class with parameters Location = {0}, Scale = {1}, DegreesOfFreedom = {2}", studentT.Location, studentT.Scale, studentT.DegreesOfFreedom);
            Console.WriteLine();

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

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

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

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

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

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

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

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

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

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

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

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

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

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

            // 4. Generate 100000 samples of the StudentT(0, 1, 1) distribution and display histogram
            Console.WriteLine(@"4. Generate 100000 samples of the StudentT(0, 1, 1) distribution and display histogram");
            var data = new double[100000];
            for (var i = 0; i < data.Length; i++)
            {
                data[i] = studentT.Sample();
            }

            ConsoleHelper.DisplayHistogram(data);

            // 5. Generate 100000 samples of the StudentT(0, 1, 5) distribution and display histogram
            Console.WriteLine(@"5. Generate 100000 samples of the StudentT(0, 1, 5) distribution and display histogram");
            studentT.DegreesOfFreedom = 5;
            for (var i = 0; i < data.Length; i++)
            {
                data[i] = studentT.Sample();
            }

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

            // 6. Generate 100000 samples of the StudentT(0, 1, 10) distribution and display histogram
            Console.WriteLine(@"6. Generate 100000 samples of the StudentT(0, 1, 10) distribution and display histogram");
            studentT.DegreesOfFreedom = 10;
            for (var i = 0; i < data.Length; i++)
            {
                data[i] = studentT.Sample();
            }

            ConsoleHelper.DisplayHistogram(data);
        }
开发者ID:jvangael,项目名称:mathnet-numerics,代码行数:88,代码来源:StudentTDistribution.cs

示例2: ValidateDensityLn

 public void ValidateDensityLn(double location, double scale, double dof, double x, double p)
 {
     var n = new StudentT(location, scale, dof);
     AssertHelpers.AlmostEqualRelative(p, n.DensityLn(x), 13);
 }
开发者ID:rookboom,项目名称:mathnet-numerics,代码行数:5,代码来源:StudentTTests.cs


注:本文中的MathNet.Numerics.Distributions.StudentT.DensityLn方法示例由纯净天空整理自Github/MSDocs等开源代码及文档管理平台,相关代码片段筛选自各路编程大神贡献的开源项目,源码版权归原作者所有,传播和使用请参考对应项目的License;未经允许,请勿转载。