@Alias(value={"invgauss","wald","de.lmu.ifi.dbs.elki.math.statistics.distribution.WaldDistribution"}) public class InverseGaussianDistribution extends AbstractDistribution
InverseGaussian(a, x) ~ scipy.stats.invgauss(a/x, x)
Our parameter scheme is in line with common literature. SciPy naming scheme
has comparable notion of location and scale across distributions. So both
have their benefits.Modifier and Type | Class and Description |
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static class |
InverseGaussianDistribution.Parameterizer
Parameterization class
|
Modifier and Type | Field and Description |
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private double |
mean
Location value
|
private double |
shape
Shape parameter
|
random
Constructor and Description |
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InverseGaussianDistribution(double mean,
double shape)
Constructor for Gaussian distribution
|
InverseGaussianDistribution(double mean,
double shape,
java.util.Random random)
Constructor for wald distribution
|
InverseGaussianDistribution(double mean,
double shape,
RandomFactory random)
Constructor for wald distribution
|
Modifier and Type | Method and Description |
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double |
cdf(double val)
Return the cumulative density function at the given value.
|
static double |
cdf(double x,
double mu,
double shape)
Cumulative probability density function (CDF) of a Wald distribution.
|
double |
getMean()
Mean parameter.
|
double |
getShape()
Shape parameter.
|
double |
logpdf(double val)
Return the log density of an existing value
|
static double |
logpdf(double x,
double mu,
double shape)
Probability density function of the Wald 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 shape)
Probability density function of the Wald distribution.
|
double |
quantile(double q)
Deprecated.
NOT YET IMPLEMENTED.
|
static double |
quantile(double x,
double mu,
double shape)
Deprecated.
NOT YET IMPLEMENTED.
|
java.lang.String |
toString()
Describe the distribution
|
public InverseGaussianDistribution(double mean, double shape, java.util.Random random)
mean
- Meanshape
- Shape parameterrandom
- Random generatorpublic InverseGaussianDistribution(double mean, double shape, RandomFactory random)
mean
- Meanshape
- Shape parameterrandom
- Random generatorpublic InverseGaussianDistribution(double mean, double shape)
mean
- Meanshape
- Shape parameterpublic double getMean()
public double getShape()
public double pdf(double val)
Distribution
val
- existing valuepublic double logpdf(double val)
Distribution
val
- existing valuepublic double cdf(double val)
Distribution
val
- existing value@Deprecated public 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 shape)
x
- The value.mu
- The mean.shape
- Shape parameterpublic static double logpdf(double x, double mu, double shape)
x
- The value.mu
- The mean.shape
- Shape parameterpublic static double cdf(double x, double mu, double shape)
x
- value to evaluate CDF atmu
- Mean valueshape
- Shape parameter@Deprecated public static double quantile(double x, double mu, double shape)
x
- value to evaluate probit function atmu
- Mean valueshape
- Shape parameterCopyright © 2019 ELKI Development Team. License information.