static double[][] GenerateRandomVector()
{
double[] excpectationVector = { 116, 102, 113, 100, 107, 110 };
double[] variance = { 1, 36, 4, 49, 16, 9 };
double[][] oilCost = new double[2][];
for (int i = 0; i < 2; i++)
{
oilCost[i] = new double[3];
for (int j = 0; j < 3; j++)
{
do
{
oilCost[i][j] = StudentT.Sample(excpectationVector[i + j], Math.Sqrt(variance[i + j]), 4);
}while (80 > oilCost[i][j] && oilCost[i][j] > 120);
}
}
return(oilCost);
}
public double getSample() // 获取当前分布样本
{
double ret = 0;
switch (DistributionName)
{
case "Normal":
ret = normalDis.Sample(); break;
case "ContinuousUniform":
ret = continuousUniformDis.Sample(); break;
case "Triangular":
ret = triangularDis.Sample(); break;
case "StudentT":
ret = studentTDis.Sample(); break;
case "DiscreteUniform":
ret = discreteUniform.Sample(); break;
}
return(ret);
}
public void CanSample()
{
var n = new StudentT();
var d = n.Sample();
}
public void FailSampleStatic(double location, double scale, double dof)
{
var d = StudentT.Sample(new Random(), location, scale, dof);
}
public void CanSampleStatic()
{
var d = StudentT.Sample(new Random(), 0.0, 1.0, 3.0);
}
public void FailSampleStatic()
{
Assert.Throws <ArgumentOutOfRangeException>(() => StudentT.Sample(new Random(0), Double.NaN, 1.0, Double.NaN));
}
/// <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);
}
public void CanSample()
{
var n = new StudentT();
var d = n.Sample();
}