Skewed |
public class SkewedGeneralizedError : IContinuousDistribution, IUnivariateDistribution, IDistribution
The SkewedGeneralizedError type exposes the following members.
Name | Description | |
---|---|---|
SkewedGeneralizedError | Initializes a new instance of the SkewedGeneralizedError class. This is a generalized error distribution with location=0.0, scale=1.0, skew=0.0 and p=2.0 (a standard normal distribution). | |
SkewedGeneralizedError(Double, Double, Double, Double) | Initializes a new instance of the SkewedGeneralizedT class with a particular location, scale, skew and kurtosis parameters. Different parameterizations result in different distributions. |
Name | Description | |
---|---|---|
Entropy | ||
Location | Gets the location (μ) of the Skewed Generalized t-distribution. | |
Maximum | ||
Mean | ||
Median | ||
Minimum | ||
Mode | ||
P | Gets the parameter that controls the kurtosis of the distribution. Range: p > 0. | |
RandomSource | Gets or sets the random number generator which is used to draw random samples. | |
Scale | Gets the scale (σ) of the Skewed Generalized t-distribution. Range: σ > 0. | |
Skew | Gets the skew (λ) of the Skewed Generalized t-distribution. Range: 1 > λ > -1. | |
Skewness | ||
StdDev | ||
Variance |
Name | Description | |
---|---|---|
CDF | ||
CumulativeDistribution | ||
Density | ||
DensityLn | ||
Equals | Determines whether the specified object is equal to the current object. (Inherited from Object) | |
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 | ||
InverseCumulativeDistribution | ||
IsValidParameterSet | Tests whether the provided values are valid parameters for this distribution. | |
MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object) | |
PDFLn | ||
Sample | ||
Sample(Double, Double, Double, Double) | Generates a sample from the Skew Generalized Error distribution. | |
Sample(Random, Double, Double, Double, Double) | Generates a sample from the Skew Generalized Error distribution. | |
Samples | ||
Samples(Double) | ||
Samples(Double, Double, Double, Double) | Generates a sequence of samples from the Skew Generalized Error distribution using inverse transform. | |
Samples(Double, Double, Double, Double, Double) | Fills an array with samples from the Skew Generalized Error distribution using inverse transform. | |
Samples(Random, Double, Double, Double, Double) | Generates a sequence of samples from the Skew Generalized Error distribution using inverse transform. | |
Samples(Random, Double, Double, Double, Double, Double) | Fills an array with samples from the Skew Generalized Error distribution using inverse transform. | |
ToString |
A string representation of the distribution.
(Overrides ObjectToString) |
This implementation is based on the R package dsgt and corresponding viginette, see https://cran.r-project.org/web/packages/sgt/vignettes/sgt.pdf. Compared to that implementation, the options for mean adjustment and variance adjustment are always true. The location (μ) is the mean of the distribution. The scale (σ) squared is the variance of the distribution.
The distribution will use the Random by default. Users can get/set the random number generator by using the RandomSource property.
The statistics classes will check all the incoming parameters whether they are in the allowed range.