public void ValidateDensity([Values(0.0, 0.0, 0.0, 0.0, -5.0, 0.0)] double lower, [Values(0.0, 0.1, 1.0, 10.0, 100.0, Double.PositiveInfinity)] double upper)
{
var n = new ContinuousUniform(lower, upper);
for (var i = 0; i < 11; i++)
{
var x = i - 5.0;
if (x >= lower && x <= upper)
{
Assert.AreEqual(1.0 / (upper - lower), n.Density(x));
}
else
{
Assert.AreEqual(0.0, n.Density(x));
}
}
}
public void ValidateDensity(double lower, double upper)
{
var n = new ContinuousUniform(lower, upper);
for (var i = 0; i < 11; i++)
{
var x = i - 5.0;
if (x >= lower && x <= upper)
{
Assert.AreEqual(1.0 / (upper - lower), n.Density(x));
}
else
{
Assert.AreEqual(0.0, n.Density(x));
}
}
}
/// <summary>
/// Run example
/// </summary>
/// <a href="http://en.wikipedia.org/wiki/Uniform_distribution_%28continuous%29">ContinuousUniform distribution</a>
public void Run()
{
// 1. Initialize the new instance of the ContinuousUniform distribution class with default parameters.
var continuousUniform = new ContinuousUniform();
Console.WriteLine(@"1. Initialize the new instance of the ContinuousUniform distribution class with parameters Lower = {0}, Upper = {1}", continuousUniform.Lower, continuousUniform.Upper);
Console.WriteLine();
// 2. Distributuion properties:
Console.WriteLine(@"2. {0} distributuion properties:", continuousUniform);
// Cumulative distribution function
Console.WriteLine(@"{0} - Сumulative distribution at location '0.3'", continuousUniform.CumulativeDistribution(0.3).ToString(" #0.00000;-#0.00000"));
// Probability density
Console.WriteLine(@"{0} - Probability density at location '0.3'", continuousUniform.Density(0.3).ToString(" #0.00000;-#0.00000"));
// Log probability density
Console.WriteLine(@"{0} - Log probability density at location '0.3'", continuousUniform.DensityLn(0.3).ToString(" #0.00000;-#0.00000"));
// Entropy
Console.WriteLine(@"{0} - Entropy", continuousUniform.Entropy.ToString(" #0.00000;-#0.00000"));
// Largest element in the domain
Console.WriteLine(@"{0} - Largest element in the domain", continuousUniform.Maximum.ToString(" #0.00000;-#0.00000"));
// Smallest element in the domain
Console.WriteLine(@"{0} - Smallest element in the domain", continuousUniform.Minimum.ToString(" #0.00000;-#0.00000"));
// Mean
Console.WriteLine(@"{0} - Mean", continuousUniform.Mean.ToString(" #0.00000;-#0.00000"));
// Median
Console.WriteLine(@"{0} - Median", continuousUniform.Median.ToString(" #0.00000;-#0.00000"));
// Mode
Console.WriteLine(@"{0} - Mode", continuousUniform.Mode.ToString(" #0.00000;-#0.00000"));
// Variance
Console.WriteLine(@"{0} - Variance", continuousUniform.Variance.ToString(" #0.00000;-#0.00000"));
// Standard deviation
Console.WriteLine(@"{0} - Standard deviation", continuousUniform.StdDev.ToString(" #0.00000;-#0.00000"));
// Skewness
Console.WriteLine(@"{0} - Skewness", continuousUniform.Skewness.ToString(" #0.00000;-#0.00000"));
Console.WriteLine();
// 3. Generate 10 samples of the ContinuousUniform distribution
Console.WriteLine(@"3. Generate 10 samples of the ContinuousUniform distribution");
for (var i = 0; i < 10; i++)
{
Console.Write(continuousUniform.Sample().ToString("N05") + @" ");
}
Console.WriteLine();
Console.WriteLine();
// 4. Generate 100000 samples of the ContinuousUniform(0, 1) distribution and display histogram
Console.WriteLine(@"4. Generate 100000 samples of the ContinuousUniform(0, 1) distribution and display histogram");
var data = new double[100000];
for (var i = 0; i < data.Length; i++)
{
data[i] = continuousUniform.Sample();
}
ConsoleHelper.DisplayHistogram(data);
Console.WriteLine();
// 5. Generate 100000 samples of the ContinuousUniform(2, 10) distribution and display histogram
Console.WriteLine(@"5. Generate 100000 samples of the ContinuousUniform(2, 10) distribution and display histogram");
continuousUniform.Upper = 10;
continuousUniform.Lower = 2;
for (var i = 0; i < data.Length; i++)
{
data[i] = continuousUniform.Sample();
}
ConsoleHelper.DisplayHistogram(data);
}
public void ValidateDensity(double lower, double upper)
{
var n = new ContinuousUniform(lower, upper);
for (int i = 0; i < 11; i++)
{
double x = i - 5.0;
if(x >= lower && x <= upper)
{
Assert.AreEqual<double>(1.0 / (upper - lower), n.Density(x));
}
else
{
Assert.AreEqual<double>(0.0, n.Density(x));
}
}
}
static void Main(string[] args)
{
// Binomial
var p = 0.174;
var n = 6;
var x = 5;
var bCdf = Binomial.CDF(p, n, x);
var bPmf = Binomial.PMF(p, n, x);
var bPmfLn = Binomial.PMFLn(p, n, x);
var b = new Binomial(p, n);
var _bCdf = b.CumulativeDistribution(x);
var _bPmf = b.Probability(x);
var _bPmfLn = b.ProbabilityLn(x);
// Normal
var mean = 1012.5;
var stdDev = 24.8069;
var x1 = 1000;
var x2 = 1025;
var nCdf = Normal.CDF(mean, stdDev, x2) - Normal.CDF(mean, stdDev, x1);
var nPdf = Normal.PDF(mean, stdDev, x2) - Normal.PDF(mean, stdDev, x1);
var nPdfLn = Normal.PDFLn(mean, stdDev, x2) - Normal.PDFLn(mean, stdDev, x1);
var resN = new List <double>();
for (int i = 950; i < 1075; i++)
{
//resN.Add(Normal.CDF(mean, stdDev, 1075) - Normal.CDF(mean, stdDev, i));
resN.Add(Normal.CDF(mean, stdDev, i));
}
var _n = new Normal(mean, stdDev);
var _nCdf = b.CumulativeDistribution(x2) - b.CumulativeDistribution(x1);
var _nPdf = b.Probability(x2) - b.Probability(x1);
var _nPdfLn = b.ProbabilityLn(x2) - b.ProbabilityLn(x1);
var nSamples = new double[100];
_n.Samples(nSamples);
// Discrete Uniform
var sqrtThree = Math.Sqrt(3);
var _mean = 2.1;
var _stdDev = 1.465;
var lower = (_mean - sqrtThree * _stdDev);
var upper = (_mean + sqrtThree * _stdDev);
var u = new ContinuousUniform(lower, upper);
var _p = u.Density(1.05);
var h = new Histogram(nSamples, 5);
Regex _regexBack = new Regex(@"(?:(?<Lower>[\d]+)? *-? *(?:(?<Upper>[\d]+)))");
var test0 = "66";
var select = test0;
if (_regexBack.IsMatch(select))
{
foreach (var match in _regexBack.Matches(select))
{
}
}
Console.ReadKey();
}
public void ValidateDensity([Values(0.0, 0.0, 0.0, 0.0, -5.0, 0.0)] double lower, [Values(0.0, 0.1, 1.0, 10.0, 100.0, Double.PositiveInfinity)] double upper)
{
var n = new ContinuousUniform(lower, upper);
for (var i = 0; i < 11; i++)
{
var x = i - 5.0;
if (x >= lower && x <= upper)
{
Assert.AreEqual(1.0 / (upper - lower), n.Density(x));
}
else
{
Assert.AreEqual(0.0, n.Density(x));
}
}
}
