Represents an exponential distribution.
Namespace: Extreme.Statistics.Distributions
Assembly: Extreme.Numerics (Extreme.Numerics)
Syntax
| Visual Basic (Declaration) |
|---|
Public Class ExponentialDistribution _ Inherits ContinuousDistribution |
| C# |
|---|
public class ExponentialDistribution : ContinuousDistribution |
| C++ |
|---|
public ref class ExponentialDistribution : public ContinuousDistribution |
Methods
| Icon | Type | Description |
|---|---|---|
 | DistributionFunction(Double) |
Evaluates the cumulative distribution function
(CDF) of this distribution for the specified value.
|
| Equals(Object) | |
 | Finalize() | |
| GetExpectedHistogram(Double[](), Double) |
Gets a Histogram whose bins contain the expected number of samples
for a given total number of samples.
|
| GetExpectedHistogram(Double, Double, Int32, Double) |
Gets a Histogram whose bins contain the expected number of samples
for a given total number of samples.
|
| GetHashCode() | Serves as a hash function for a particular type. |
 | GetRandomVariate(Random, Double) |
Returns a single random variate from an exponential distribution
with the specified scale parameter..
|
| GetRandomVariate(Random) |
Returns a random sample from the distribution.
|
| GetRandomVariates(Random, Vector) |
Fills a Vector with random numbers.
|
| GetRandomVariates(Random, Double[]()) |
Fills a Double array with random numbers.
|
| GetRandomVariates(Random, Double[](), Int32, Int32) |
Fills a Double array with random numbers.
|
| GetRandomVariates(Random, Vector, Int32, Int32) |
Fills a Double array with random numbers.
|
| GetType() | Gets the Type of the current instance. |
| InverseDistributionFunction(Double) |
Returns the sample value at the specified percentile.
|
| MemberwiseClone() | Creates a shallow copy of the current Object. |
| Probability(Double, Double) |
Returns the probability that a sample taken from the
distribution lies inside the specified interval.
|
| ProbabilityDensityFunction(Double) |
Returns the value of the probability density function
(PDF) of this distribution for the specified value.
|
| SurvivorDistributionFunction(Double) |
Evaluates the survivor distribution function
(SDF) of this distribution for the specified value.
|
| ToString() |
Constructors
| Icon | Type | Description |
|---|---|---|
| ExponentialDistributionNew(NumericalVariable) |
Estimates the parameters of the distribution of a variable assuming it follows an exponential distribution.
|
| ExponentialDistributionNew(Double) |
Constructs a new ExponentialDistribution.
|
Properties
| Icon | Type | Description |
|---|---|---|
 | InterQuartileRange |
Returns the inter-quartile range of this distribution.
|
| IsSymmetrical |
Gets a value that indicates whether the distribution is known to be symmetrical around the mean.
|
| Kurtosis |
Gets the kurtosis of the distribution.
|
| Mean |
Gets the mean or expectation value of the distribution.
|
| ScaleParameter |
Gets the scale parameter of the distribution.
|
| Skewness |
Gets the skewness of the distribution.
|
| StandardDeviation |
Gets the standard deviation of the distribution.
|
| Variance |
Gets the variance of the distribution.
|
Remarks
The exponential distribution characterizes the waiting time for an event when the probability of the event occurring is constant.
The exponential distribution has one parameter: ScaleParameter, which corresponds to the waiting time until an event occurs.
The discrete form of the exponential distribution is the GeometricDistribution.
The exponential distribution is also complementary to the PoissonDistribution. Where the Poisson distribution models the number of occurrances in a given time interval, the exponential distribution models the time until the next occurrance.
Examples
The time until an event occurs when the probability doesn't change with time
follows an exponential distribution.
Inheritance Hierarchy
System.Object
Extreme.Statistics.Distributions.Distribution
Extreme.Statistics.Distributions.ContinuousDistribution
Extreme.Statistics.Distributions.ExponentialDistribution
Extreme.Statistics.Distributions.Distribution
Extreme.Statistics.Distributions.ContinuousDistribution
Extreme.Statistics.Distributions.ExponentialDistribution
See Also
