ExponentialDistribution Class

[SerializableAttribute]
public class ExponentialDistribution : UnivariateContinuousDistribution, 
	IFittableDistribution<double, IFittingOptions>, IFittable<double, IFittingOptions>, 
	IFittable<double>, IFittableDistribution<double>, IDistribution<double>, 
	IDistribution, ICloneable, ISampleableDistribution<double>, IRandomNumberGenerator<double>

<SerializableAttribute>
Public Class ExponentialDistribution
	Inherits UnivariateContinuousDistribution
	Implements IFittableDistribution(Of Double, IFittingOptions), 
	IFittable(Of Double, IFittingOptions), IFittable(Of Double), 
	IFittableDistribution(Of Double), IDistribution(Of Double), IDistribution, 
	ICloneable, ISampleableDistribution(Of Double), IRandomNumberGenerator(Of Double)

// Create an Exponential distribution with λ = 0.42
var exp = new ExponentialDistribution(rate: 0.42);

// Common measures
double mean = exp.Mean;     // 2.3809523809523809
double median = exp.Median; // 1.6503504299046317
double var = exp.Variance;  // 5.6689342403628125

// Cumulative distribution functions
double cdf  = exp.DistributionFunction(x: 0.27);          // 0.10720652870550407
double ccdf = exp.ComplementaryDistributionFunction(x: 0.27); // 0.89279347129449593
double icdf = exp.InverseDistributionFunction(p: cdf);        // 0.27

// Probability density functions
double pdf  = exp.ProbabilityDensityFunction(x: 0.27);    // 0.3749732579436883
double lpdf = exp.LogProbabilityDensityFunction(x: 0.27); // -0.98090056770472311

// Hazard (failure rate) functions
double hf = exp.HazardFunction(x: 0.27);            // 0.42
double chf = exp.CumulativeHazardFunction(x: 0.27); // 0.1134

// String representation
string str = exp.ToString(CultureInfo.InvariantCulture); // Exp(x; λ = 0.42)

// Create an Exponential distribution with λ = 2.5
var exp = new ExponentialDistribution(rate: 2.5);

// Generate a million samples from this distribution:
double[] samples = target.Generate(1000000);

// Create a default exponential distribution
var newExp = new ExponentialDistribution();

// Fit the samples
newExp.Fit(samples);

// Check the estimated parameters
double rate = newExp.Rate; // 2.5