public void ValidateDensity(
[Values(1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0)] double shape,
[Values(0.1, 0.1, 0.1, 1.0, 1.0, 1.0, 10.0, 10.0, 10.0, 1.0, 1.0, 1.0)] double scale,
[Values(0.0, 1.0, 10.0, 0.0, 1.0, 10.0, 0.0, 1.0, 10.0, 0.0, 1.0, 10.0)] double x,
[Values(10.0, 0.00045399929762484851535591515560550610237918088866565, 3.7200759760208359629596958038631183373588922923768e-43, 1.0, 0.36787944117144232159552377016146086744581113103177, 0.000045399929762484851535591515560550610237918088866565, 0.0, 9.9999999990000000000499999999983333333333750000000e-10, 0.36787944117144232159552377016146086744581113103177, 0.0, 3.6787944117144232159552377016146086744581113103177, 0.0)] double pdf)
{
var n = new Weibull(shape, scale);
AssertHelpers.AlmostEqual(pdf, n.Density(x), 14);
}
public void ValidateDensity(
[Values(1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0)] double shape,
[Values(0.1, 0.1, 0.1, 1.0, 1.0, 1.0, 10.0, 10.0, 10.0, 1.0, 1.0, 1.0)] double scale,
[Values(0.0, 1.0, 10.0, 0.0, 1.0, 10.0, 0.0, 1.0, 10.0, 0.0, 1.0, 10.0)] double x,
[Values(10.0, 0.00045399929762484851535591515560550610237918088866565, 3.7200759760208359629596958038631183373588922923768e-43, 1.0, 0.36787944117144232159552377016146086744581113103177, 0.000045399929762484851535591515560550610237918088866565, 0.0, 9.9999999990000000000499999999983333333333750000000e-10, 0.36787944117144232159552377016146086744581113103177, 0.0, 3.6787944117144232159552377016146086744581113103177, 0.0)] double pdf)
{
var n = new Weibull(shape, scale);
AssertHelpers.AlmostEqual(pdf, n.Density(x), 14);
}
public void ValidateDensity(double shape, double scale, double x, double pdf)
{
var n = new Weibull(shape, scale);
AssertHelpers.AlmostEqualRelative(pdf, n.Density(x), 13);
}
public void ValidateDensity(double shape, double scale, double x, double pdf)
{
var n = new Weibull(shape, scale);
AssertHelpers.AlmostEqual(pdf, n.Density(x), 14);
}
/// <summary>
/// Run example
/// </summary>
/// <a href="http://en.wikipedia.org/wiki/Weibull_distribution">Weibull distribution</a>
public void Run()
{
// 1. Initialize the new instance of the Weibull distribution class with parameters Scale = 1, Shape = 0.5
var weibull = new Weibull(0.5, 1);
Console.WriteLine(@"1. Initialize the new instance of the Weibull distribution class with parameterы Scale = {0}, Shape = {1}", weibull.Scale, weibull.Shape);
Console.WriteLine();
// 2. Distributuion properties:
Console.WriteLine(@"2. {0} distributuion properties:", weibull);
// Cumulative distribution function
Console.WriteLine(@"{0} - Сumulative distribution at location '0.3'", weibull.CumulativeDistribution(0.3).ToString(" #0.00000;-#0.00000"));
// Probability density
Console.WriteLine(@"{0} - Probability density at location '0.3'", weibull.Density(0.3).ToString(" #0.00000;-#0.00000"));
// Log probability density
Console.WriteLine(@"{0} - Log probability density at location '0.3'", weibull.DensityLn(0.3).ToString(" #0.00000;-#0.00000"));
// Entropy
Console.WriteLine(@"{0} - Entropy", weibull.Entropy.ToString(" #0.00000;-#0.00000"));
// Largest element in the domain
Console.WriteLine(@"{0} - Largest element in the domain", weibull.Maximum.ToString(" #0.00000;-#0.00000"));
// Smallest element in the domain
Console.WriteLine(@"{0} - Smallest element in the domain", weibull.Minimum.ToString(" #0.00000;-#0.00000"));
// Mean
Console.WriteLine(@"{0} - Mean", weibull.Mean.ToString(" #0.00000;-#0.00000"));
// Median
Console.WriteLine(@"{0} - Median", weibull.Median.ToString(" #0.00000;-#0.00000"));
// Mode
Console.WriteLine(@"{0} - Mode", weibull.Mode.ToString(" #0.00000;-#0.00000"));
// Variance
Console.WriteLine(@"{0} - Variance", weibull.Variance.ToString(" #0.00000;-#0.00000"));
// Standard deviation
Console.WriteLine(@"{0} - Standard deviation", weibull.StdDev.ToString(" #0.00000;-#0.00000"));
// Skewness
Console.WriteLine(@"{0} - Skewness", weibull.Skewness.ToString(" #0.00000;-#0.00000"));
Console.WriteLine();
// 3. Generate 10 samples of the Weibull distribution
Console.WriteLine(@"3. Generate 10 samples of the Weibull distribution");
for (var i = 0; i < 10; i++)
{
Console.Write(weibull.Sample().ToString("N05") + @" ");
}
Console.WriteLine();
Console.WriteLine();
// 4. Generate 100000 samples of the Weibull(0.5, 1) distribution and display histogram
Console.WriteLine(@"4. Generate 100000 samples of the Weibull(0.5, 1) distribution and display histogram");
var data = new double[100000];
for (var i = 0; i < data.Length; i++)
{
data[i] = weibull.Sample();
}
ConsoleHelper.DisplayHistogram(data);
Console.WriteLine();
// 5. Generate 100000 samples of the Weibull(1.5, 1) distribution and display histogram
Console.WriteLine(@"5. Generate 100000 samples of the Weibull(1.5, 1) distribution and display histogram");
weibull.Shape = 1.5;
for (var i = 0; i < data.Length; i++)
{
data[i] = weibull.Sample();
}
ConsoleHelper.DisplayHistogram(data);
Console.WriteLine();
// 6. Generate 100000 samples of the Weibull(5, 1) distribution and display histogram
Console.WriteLine(@"6. Generate 100000 samples of the Weibull(5, 1) distribution and display histogram");
weibull.Shape = 5;
for (var i = 0; i < data.Length; i++)
{
data[i] = weibull.Sample();
}
ConsoleHelper.DisplayHistogram(data);
}