/// <summary>
/// Run example
/// </summary>
/// <a href="http://en.wikipedia.org/wiki/Geometric_distribution">Geometric distribution</a>
public void Run()
{
// 1. Initialize the new instance of the Geometric distribution class with parameter P = 0.2
var geometric = new Geometric(0.2);
Console.WriteLine(@"1. Initialize the new instance of the Geometric distribution class with parameter P = {0}", geometric.P);
Console.WriteLine();
// 2. Distributuion properties:
Console.WriteLine(@"2. {0} distributuion properties:", geometric);
// Cumulative distribution function
Console.WriteLine(@"{0} - Сumulative distribution at location '3'", geometric.CumulativeDistribution(3).ToString(" #0.00000;-#0.00000"));
// Probability density
Console.WriteLine(@"{0} - Probability mass at location '3'", geometric.Probability(3).ToString(" #0.00000;-#0.00000"));
// Log probability density
Console.WriteLine(@"{0} - Log probability mass at location '3'", geometric.ProbabilityLn(3).ToString(" #0.00000;-#0.00000"));
// Entropy
Console.WriteLine(@"{0} - Entropy", geometric.Entropy.ToString(" #0.00000;-#0.00000"));
// Largest element in the domain
Console.WriteLine(@"{0} - Largest element in the domain", geometric.Maximum.ToString(" #0.00000;-#0.00000"));
// Smallest element in the domain
Console.WriteLine(@"{0} - Smallest element in the domain", geometric.Minimum.ToString(" #0.00000;-#0.00000"));
// Mean
Console.WriteLine(@"{0} - Mean", geometric.Mean.ToString(" #0.00000;-#0.00000"));
// Median
Console.WriteLine(@"{0} - Median", geometric.Median.ToString(" #0.00000;-#0.00000"));
// Mode
Console.WriteLine(@"{0} - Mode", geometric.Mode.ToString(" #0.00000;-#0.00000"));
// Variance
Console.WriteLine(@"{0} - Variance", geometric.Variance.ToString(" #0.00000;-#0.00000"));
// Standard deviation
Console.WriteLine(@"{0} - Standard deviation", geometric.StdDev.ToString(" #0.00000;-#0.00000"));
// Skewness
Console.WriteLine(@"{0} - Skewness", geometric.Skewness.ToString(" #0.00000;-#0.00000"));
Console.WriteLine();
// 3. Generate 10 samples of the Geometric distribution
Console.WriteLine(@"3. Generate 10 samples of the Geometric distribution");
for (var i = 0; i < 10; i++)
{
Console.Write(geometric.Sample().ToString("N05") + @" ");
}
Console.WriteLine();
Console.WriteLine();
// 4. Generate 100000 samples of the Geometric(0.2, 20) distribution and display histogram
Console.WriteLine(@"4. Generate 100000 samples of the Geometric(0.2, 20) distribution and display histogram");
var data = new double[100000];
for (var i = 0; i < data.Length; i++)
{
data[i] = geometric.Sample();
}
ConsoleHelper.DisplayHistogram(data);
Console.WriteLine();
// 5. Generate 100000 samples of the Geometric(0.5) distribution and display histogram
Console.WriteLine(@"5. Generate 100000 samples of the Geometric(0.5) distribution and display histogram");
geometric.P = 0.5;
for (var i = 0; i < data.Length; i++)
{
data[i] = geometric.Sample();
}
ConsoleHelper.DisplayHistogram(data);
Console.WriteLine();
// 6. Generate 100000 samples of the Geometric(0.8) distribution and display histogram
Console.WriteLine(@"6. Generate 100000 samples of the Geometric(0.8) distribution and display histogram");
geometric.P = 0.8;
for (var i = 0; i < data.Length; i++)
{
data[i] = geometric.Sample();
}
ConsoleHelper.DisplayHistogram(data);
}
public void ValidateProbabilityLn(double p, int x, double pln)
{
var d = new Geometric(p);
if (x > 0)
{
Assert.AreEqual(((x - 1) * Math.Log(1.0 - p)) + Math.Log(p), d.ProbabilityLn(x));
}
else
{
Assert.AreEqual(Double.NegativeInfinity, d.ProbabilityLn(x));
}
}