public class BivariateEVDNegativeBilogistic extends AbstractBivariateEVD
evd:dbvnegbilog
, evd:pbvnegbilog
, evd:rbvnegbilog
,
evd:hbvnegbilog
, evd:abvnegbilog
, evd:ccbvevd
.Constructor and Description |
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BivariateEVDNegativeBilogistic(double alpha,
double beta) |
BivariateEVDNegativeBilogistic(double alpha,
double beta,
GeneralizedEVD marginal) |
BivariateEVDNegativeBilogistic(double alpha,
double beta,
GeneralizedEVD marginal1,
GeneralizedEVD marginal2) |
Modifier and Type | Method and Description |
---|---|
double |
cdf(double x1,
double x2)
The joint distribution function \(F_{X_1,X_2}(x_1,x_2) = Pr(X_1 \le x_1, X_2 \le x_2)\).
|
double |
conditionalCopula(double x1,
double x2)
The conditional copula function conditioning on either margin.
|
double |
density(double x1,
double x2)
The joint distribution density \(f_{X_1,X_2}(x_1,x_2)\).
|
double |
dependence(double x)
The dependence function \(A\) for the parametric bivariate extreme value model.
|
double[] |
nextVector()
Get the next random vector.
|
void |
seed(long... seeds)
Seed the random number/vector/scenario generator to produce repeatable experiments.
|
double |
spectralDensity(double x)
The density \(h\) of the spectral measure \(H\) on the interval (0,1).
|
covariance, entropy, mean, mode, moment
cdf, density
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
cdf, density
public BivariateEVDNegativeBilogistic(double alpha, double beta)
public BivariateEVDNegativeBilogistic(double alpha, double beta, GeneralizedEVD marginal)
public BivariateEVDNegativeBilogistic(double alpha, double beta, GeneralizedEVD marginal1, GeneralizedEVD marginal2)
public double density(double x1, double x2)
BivariateProbabilityDistribution
x1
- the value drawn from \(X_1\)x2
- the value drawn from \(X_2\)public double cdf(double x1, double x2)
BivariateProbabilityDistribution
x1
- the value drawn from \(X_1\)x2
- the value drawn from \(X_2\)public double spectralDensity(double x)
BivariateEVD
x
- xpublic double dependence(double x)
BivariateEVD
x
- xpublic double conditionalCopula(double x1, double x2)
BivariateEVD
x1
- an observation from \(U_1\)x2
- an observation from \(U_2\)public double[] nextVector()
RandomVectorGenerator
public void seed(long... seeds)
Seedable
seeds
- the seedsCopyright © 2010-2020 NM FinTech Ltd.. All Rights Reserved.