Inverse |
[Missing <summary> documentation for "T:Altaxo.Calc.Distributions.InverseGaussian"]
public class InverseGaussian : IContinuousDistribution, IUnivariateDistribution, IDistribution
The InverseGaussian type exposes the following members.
Name | Description | |
---|---|---|
InverseGaussian | Initializes a new instance of the InverseGaussian class. |
Name | Description | |
---|---|---|
Entropy | Gets the entropy of the Inverse Gaussian distribution (currently not supported). | |
Kurtosis | Gets the kurtosis of the Inverse Gaussian distribution. | |
Lambda | Gets the shape (λ) of the distribution. Range: λ > 0. | |
Maximum | Gets the maximum of the Inverse Gaussian distribution. | |
Mean | Gets the mean of the Inverse Gaussian distribution. | |
Median | Gets the median of the Inverse Gaussian distribution. No closed form analytical expression exists, so this value is approximated numerically and can throw an exception. | |
Minimum | Gets the minimum of the Inverse Gaussian distribution. | |
Mode | Gets the mode of the Inverse Gaussian distribution. | |
Mu | Gets the mean (μ) of the distribution. Range: μ > 0. | |
RandomSource | Gets the random number generator which is used to draw random samples. | |
Skewness | Gets the skewness of the Inverse Gaussian distribution. | |
StdDev | Gets the standard deviation of the Inverse Gaussian distribution. | |
Variance | Gets the variance of the Inverse Gaussian distribution. |
Name | Description | |
---|---|---|
CDF | Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x). | |
CumulativeDistribution | Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x). | |
Density | Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x. | |
DensityLn | Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x). | |
Equals | Determines whether the specified object is equal to the current object. (Inherited from Object) | |
Estimate | Estimates the Inverse Gaussian parameters from sample data with maximum-likelihood. | |
Finalize | Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object) | |
GetHashCode | Serves as the default hash function. (Inherited from Object) | |
GetType | Gets the Type of the current instance. (Inherited from Object) | |
InvCDF(Double) | Computes the inverse cumulative distribution (CDF) of the distribution at p, i.e. solving for P(X ≤ x) = p. | |
InvCDF(Double, Double, Double) | Computes the inverse cumulative distribution (CDF) of the distribution at p, i.e. solving for P(X ≤ x) = p. | |
IsValidParameterSet | Tests whether the provided values are valid parameters for this distribution. | |
MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object) | |
Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x. | ||
PDFLn | Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x). | |
Sample | Generates a sample from the inverse Gaussian distribution. | |
Sample(Random, Double, Double) | Generates a sample from the inverse Gaussian distribution. | |
Samples | Generates a sequence of samples from the inverse Gaussian distribution. | |
Samples(Double) | Fills an array with samples generated from the distribution. | |
Samples(Random, Double, Double) | Generates a sequence of samples from the Burr distribution. | |
Samples(Random, Double, Double, Double) | Fills an array with samples generated from the distribution. | |
ToString |
A string representation of the distribution.
(Overrides ObjectToString) |