public void ValidateProbabilityLn(double p, int x, double dln)
{
var b = new Bernoulli(p);
AssertEx.AreEqual(dln, b.ProbabilityLn(x));
}
public void ValidateProbabilityLn(
[Values(0.0, 0.0, 0.0, 0.0, 0.3, 0.3, 0.3, 0.3, 1.0, 1.0, 1.0, 1.0)] double p,
[Values(-1, 0, 1, 2, -1, 0, 1, 2, -1, 0, 1, 2)] int x,
[Values(Double.NegativeInfinity, 0.0, Double.NegativeInfinity, Double.NegativeInfinity, Double.NegativeInfinity, -0.35667494393873244235395440410727451457180907089949815, -1.2039728043259360296301803719337238685164245381839102, Double.NegativeInfinity, Double.NegativeInfinity, Double.NegativeInfinity, 0.0, Double.NegativeInfinity)] double dln)
{
var b = new Bernoulli(p);
Assert.AreEqual(dln, b.ProbabilityLn(x));
}
public void ValidateProbabilityLn(double p, int x, double dln)
{
var b = new Bernoulli(p);
Assert.AreEqual(dln, b.ProbabilityLn(x));
}
/// <summary>
/// Run example
/// </summary>
/// <a href="http://en.wikipedia.org/wiki/Bernoulli_distribution">Bernoulli distribution</a>
public void Run()
{
// 1. Initialize the new instance of the Bernoulli distribution class with parameter P = 0.2
var bernoulli = new Bernoulli(0.2);
Console.WriteLine(@"1. Initialize the new instance of the Bernoulli distribution class with parameter P = {0}", bernoulli.P);
Console.WriteLine();
// 2. Distributuion properties:
Console.WriteLine(@"2. {0} distributuion properties:", bernoulli);
// Cumulative distribution function
Console.WriteLine(@"{0} - Сumulative distribution at location '3'", bernoulli.CumulativeDistribution(3).ToString(" #0.00000;-#0.00000"));
// Probability density
Console.WriteLine(@"{0} - Probability mass at location '3'", bernoulli.Probability(3).ToString(" #0.00000;-#0.00000"));
// Log probability density
Console.WriteLine(@"{0} - Log probability mass at location '3'", bernoulli.ProbabilityLn(3).ToString(" #0.00000;-#0.00000"));
// Entropy
Console.WriteLine(@"{0} - Entropy", bernoulli.Entropy.ToString(" #0.00000;-#0.00000"));
// Largest element in the domain
Console.WriteLine(@"{0} - Largest element in the domain", bernoulli.Maximum.ToString(" #0.00000;-#0.00000"));
// Smallest element in the domain
Console.WriteLine(@"{0} - Smallest element in the domain", bernoulli.Minimum.ToString(" #0.00000;-#0.00000"));
// Mean
Console.WriteLine(@"{0} - Mean", bernoulli.Mean.ToString(" #0.00000;-#0.00000"));
// Mode
Console.WriteLine(@"{0} - Mode", bernoulli.Mode.ToString(" #0.00000;-#0.00000"));
// Variance
Console.WriteLine(@"{0} - Variance", bernoulli.Variance.ToString(" #0.00000;-#0.00000"));
// Standard deviation
Console.WriteLine(@"{0} - Standard deviation", bernoulli.StdDev.ToString(" #0.00000;-#0.00000"));
// Skewness
Console.WriteLine(@"{0} - Skewness", bernoulli.Skewness.ToString(" #0.00000;-#0.00000"));
Console.WriteLine();
// 3. Generate 10 samples of the Bernoulli distribution
Console.WriteLine(@"3. Generate 10 samples of the Bernoulli distribution");
for (var i = 0; i < 10; i++)
{
Console.Write(bernoulli.Sample().ToString("N05") + @" ");
}
Console.WriteLine();
Console.WriteLine();
// 4. Generate 100000 samples of the Bernoulli(0.2) distribution and display histogram
Console.WriteLine(@"4. Generate 100000 samples of the Bernoulli(0.2) distribution and display histogram");
var data = new int[100000];
Bernoulli.Samples(data, 0.2);
ConsoleHelper.DisplayHistogram(data);
Console.WriteLine();
// 5. Generate 100000 samples of the Bernoulli(4) distribution and display histogram
Console.WriteLine(@"5. Generate 100000 samples of the Bernoulli(0.9) distribution and display histogram");
Bernoulli.Samples(data, 0.9);
ConsoleHelper.DisplayHistogram(data);
Console.WriteLine();
// 6. Generate 100000 samples of the Bernoulli(8) distribution and display histogram
Console.WriteLine(@"6. Generate 100000 samples of the Bernoulli(0.5) distribution and display histogram");
Bernoulli.Samples(data, 0.5);
ConsoleHelper.DisplayHistogram(data);
}