@Reference(authors="J. R. M. Hosking, J. R. Wallis", title="Regional frequency analysis: an approach based on L-moments", booktitle="Regional frequency analysis: an approach based on L-moments", url="https://doi.org/10.1017/CBO9780511529443", bibkey="doi:10.1017/CBO9780511529443") public class SkewGeneralizedNormalDistribution extends AbstractDistribution
This is one kind of generalized normal distributions. Note that there are multiple that go by the name of a "Generalized Normal Distribution"; this is what is currently called "version 2" in English Wikipedia.
Reference:
J. R. M. Hosking, J. R. Wallis
Regional frequency analysis: an approach based on L-moments
Modifier and Type | Class and Description |
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static class |
SkewGeneralizedNormalDistribution.Parameterizer
Parameterization class
|
Modifier and Type | Field and Description |
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private double |
loc
Location.
|
private double |
scale
Scale.
|
private double |
skew
Skew.
|
random
Constructor and Description |
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SkewGeneralizedNormalDistribution(double loc,
double scale,
double skew)
Constructor for Gaussian distribution
|
SkewGeneralizedNormalDistribution(double loc,
double scale,
double skew,
java.util.Random random)
Constructor for Gaussian distribution
|
SkewGeneralizedNormalDistribution(double loc,
double scale,
double skew,
RandomFactory random)
Constructor for Gaussian distribution
|
Modifier and Type | Method and Description |
---|---|
double |
cdf(double val)
Return the cumulative density function at the given value.
|
static double |
cdf(double x,
double mu,
double sigma,
double skew)
Cumulative probability density function (CDF) of a normal distribution.
|
double |
getLocation()
Get the location parameter
|
double |
getScale()
Get the scale parameter
|
double |
getSkew()
Get the skew parameter.
|
double |
logpdf(double val)
Return the log density of an existing value
|
static double |
logpdf(double x,
double mu,
double sigma,
double skew)
Probability density function of the skewed normal distribution.
|
double |
nextRandom()
Generate a new random value
|
double |
pdf(double val)
Return the density of an existing value
|
static double |
pdf(double x,
double mu,
double sigma,
double skew)
Probability density function of the skewed normal distribution.
|
double |
quantile(double q)
Quantile aka probit (for normal) aka inverse CDF (invcdf, cdf^-1) function.
|
static double |
quantile(double x,
double mu,
double sigma,
double skew)
Inverse cumulative probability density function (probit) of a normal
distribution.
|
java.lang.String |
toString()
Describe the distribution
|
private double loc
private double scale
private double skew
public SkewGeneralizedNormalDistribution(double loc, double scale, double skew, java.util.Random random)
loc
- Locationscale
- Scaleskew
- Skewrandom
- Random generatorpublic SkewGeneralizedNormalDistribution(double loc, double scale, double skew, RandomFactory random)
loc
- Locationscale
- Scaleskew
- Skewrandom
- Random generatorpublic SkewGeneralizedNormalDistribution(double loc, double scale, double skew)
loc
- Locationscale
- Scaleskew
- Skewpublic double getLocation()
public double getScale()
public double getSkew()
public double pdf(double val)
Distribution
val
- existing valuepublic double logpdf(double val)
Distribution
val
- existing valuepublic double cdf(double val)
Distribution
val
- existing valuepublic double quantile(double q)
Distribution
q
- Quantile to findpublic double nextRandom()
Distribution
nextRandom
in interface Distribution
nextRandom
in class AbstractDistribution
public java.lang.String toString()
Distribution
toString
in interface Distribution
toString
in class java.lang.Object
public static double pdf(double x, double mu, double sigma, double skew)
x
- The value.mu
- The mean.sigma
- The standard deviation.public static double logpdf(double x, double mu, double sigma, double skew)
x
- The value.mu
- The mean.sigma
- The standard deviation.public static double cdf(double x, double mu, double sigma, double skew)
x
- value to evaluate CDF atmu
- Mean valuesigma
- Standard deviation.public static double quantile(double x, double mu, double sigma, double skew)
x
- value to evaluate probit function atmu
- Mean valuesigma
- Standard deviation.Copyright © 2019 ELKI Development Team. License information.