public class BivariateEVDAsymmetricMixed extends AbstractBivariateEVD
evd::dbvamix, evd::pbvamix, evd::rbvamix, evd::hbvamix,
evd::abvamix, evd::ccbvevd.| Constructor and Description |
|---|
BivariateEVDAsymmetricMixed(double alpha,
double beta) |
BivariateEVDAsymmetricMixed(double alpha,
double beta,
GeneralizedEVD marginal) |
BivariateEVDAsymmetricMixed(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, momentcdf, densityclone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitcdf, densitypublic BivariateEVDAsymmetricMixed(double alpha,
double beta)
public BivariateEVDAsymmetricMixed(double alpha,
double beta,
GeneralizedEVD marginal)
public BivariateEVDAsymmetricMixed(double alpha,
double beta,
GeneralizedEVD marginal1,
GeneralizedEVD marginal2)
public double density(double x1,
double x2)
BivariateProbabilityDistributionx1 - the value drawn from \(X_1\)x2 - the value drawn from \(X_2\)public double cdf(double x1,
double x2)
BivariateProbabilityDistributionx1 - the value drawn from \(X_1\)x2 - the value drawn from \(X_2\)public double spectralDensity(double x)
BivariateEVDx - xpublic double dependence(double x)
BivariateEVDx - xpublic double conditionalCopula(double x1,
double x2)
BivariateEVDx1 - an observation from \(U_1\)x2 - an observation from \(U_2\)public double[] nextVector()
RandomVectorGeneratorpublic void seed(long... seeds)
Seedableseeds - the seedsCopyright © 2010-2020 NM FinTech Ltd.. All Rights Reserved.