本文整理汇总了C#中MathNet.Numerics.Distributions.Gamma.CumulativeDistribution方法的典型用法代码示例。如果您正苦于以下问题：C# Gamma.CumulativeDistribution方法的具体用法？C# Gamma.CumulativeDistribution怎么用？C# Gamma.CumulativeDistribution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类MathNet.Numerics.Distributions.Gamma的用法示例。
在下文中一共展示了Gamma.CumulativeDistribution方法的4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: TestStarUniformDistribution
public void TestStarUniformDistribution()
{
IContinuousDistribution distribution = new Gamma(9, 1/5000.0);
Console.WriteLine(distribution.CumulativeDistribution(30000));
//IContinuousDistribution distribution = new Gamma(3, 0.05);
for (double d = 0; d < 50000; d = d + 1000)
{
//Console.WriteLine(Gamma.PDF(3, 0.05, d));
//Console.WriteLine(Gamma.CDF(3, 0.05, d));
Console.WriteLine("" + d + ": " + distribution.CumulativeDistribution(d));
}
}示例2: ValidateCumulativeDistribution
public void ValidateCumulativeDistribution(int shape, double invScale, double x, double cdf)
{
var gamma = new Gamma(shape, invScale);
Assert.That(gamma.CumulativeDistribution(x), Is.EqualTo(cdf).Within(13));
Assert.That(Gamma.CDF(shape, invScale, x), Is.EqualTo(cdf).Within(13));
}示例3: Run
/// <summary>
/// Run example
/// </summary>
/// <a href="http://en.wikipedia.org/wiki/Gamma_distribution">Gamma distribution</a>
public void Run()
{
// 1. Initialize the new instance of the Gamma distribution class with parameter Shape = 1, Scale = 0.5.
var gamma = new Gamma(1, 2.0);
Console.WriteLine(@"1. Initialize the new instance of the Gamma distribution class with parameters Shape = {0}, Scale = {1}", gamma.Shape, gamma.Scale);
Console.WriteLine();
// 2. Distributuion properties:
Console.WriteLine(@"2. {0} distributuion properties:", gamma);
// Cumulative distribution function
Console.WriteLine(@"{0} - Сumulative distribution at location '0.3'", gamma.CumulativeDistribution(0.3).ToString(" #0.00000;-#0.00000"));
// Probability density
Console.WriteLine(@"{0} - Probability density at location '0.3'", gamma.Density(0.3).ToString(" #0.00000;-#0.00000"));
// Log probability density
Console.WriteLine(@"{0} - Log probability density at location '0.3'", gamma.DensityLn(0.3).ToString(" #0.00000;-#0.00000"));
// Entropy
Console.WriteLine(@"{0} - Entropy", gamma.Entropy.ToString(" #0.00000;-#0.00000"));
// Largest element in the domain
Console.WriteLine(@"{0} - Largest element in the domain", gamma.Maximum.ToString(" #0.00000;-#0.00000"));
// Smallest element in the domain
Console.WriteLine(@"{0} - Smallest element in the domain", gamma.Minimum.ToString(" #0.00000;-#0.00000"));
// Mean
Console.WriteLine(@"{0} - Mean", gamma.Mean.ToString(" #0.00000;-#0.00000"));
// Mode
Console.WriteLine(@"{0} - Mode", gamma.Mode.ToString(" #0.00000;-#0.00000"));
// Variance
Console.WriteLine(@"{0} - Variance", gamma.Variance.ToString(" #0.00000;-#0.00000"));
// Standard deviation
Console.WriteLine(@"{0} - Standard deviation", gamma.StdDev.ToString(" #0.00000;-#0.00000"));
// Skewness
Console.WriteLine(@"{0} - Skewness", gamma.Skewness.ToString(" #0.00000;-#0.00000"));
Console.WriteLine();
// 3. Generate 10 samples of the Gamma distribution
Console.WriteLine(@"3. Generate 10 samples of the Gamma distribution");
for (var i = 0; i < 10; i++)
{
Console.Write(gamma.Sample().ToString("N05") + @" ");
}
Console.WriteLine();
Console.WriteLine();
// 4. Generate 100000 samples of the Gamma(1, 2) distribution and display histogram
Console.WriteLine(@"4. Generate 100000 samples of the Gamma(1, 2) distribution and display histogram");
var data = new double[100000];
Gamma.Samples(data, 1, 2);
ConsoleHelper.DisplayHistogram(data);
Console.WriteLine();
// 5. Generate 100000 samples of the Gamma(8) distribution and display histogram
Console.WriteLine(@"5. Generate 100000 samples of the Gamma(5, 1) distribution and display histogram");
Gamma.Samples(data, 5, 1);
ConsoleHelper.DisplayHistogram(data);
}示例4: ValidateCumulativeDistribution
public void ValidateCumulativeDistribution(int shape, double invScale, double x, double cdf)
{
var n = new Gamma(shape, invScale);
AssertHelpers.AlmostEqual(cdf, n.CumulativeDistribution(x), 14);
AssertHelpers.AlmostEqual(cdf, Gamma.CDF(shape, invScale, x), 14);
}