# SuanShu, a Java numerical and statistical library

com.numericalmethod.suanshu.stats.evt.markovchain

## Class ExtremeValueMC

• java.lang.Object
• com.numericalmethod.suanshu.stats.evt.markovchain.ExtremeValueMC
• All Implemented Interfaces:
RandomNumberGenerator, Seedable

public class ExtremeValueMC
extends Object
implements RandomNumberGenerator
Simulation of first order extreme value Markov chains such that each pair of consecutive values has the dependence structure of given bivariate extreme value distributions.

The R equivalent function is evd::evmc.

• ### Nested Class Summary

Nested Classes
Modifier and Type Class and Description
static class  ExtremeValueMC.MarginalDistributionType
Types of marginal distribution of each simulated value.
• ### Constructor Summary

Constructors
Constructor and Description
ExtremeValueMC(BivariateEVD bevd, ExtremeValueMC.MarginalDistributionType marginalType)
Create an instance with a given bivariate distribution that defines the dependence structure between two consecutive simulated values, and uses UniformRNG for random number generation.
ExtremeValueMC(BivariateEVD bivariate, ExtremeValueMC.MarginalDistributionType marginalType, RandomNumberGenerator uniformRng)
Create an instance with a given bivariate distribution that defines the dependence structure between two consecutive simulated values, and a uniform random number generator.
• ### Method Summary

All Methods
Modifier and Type Method and Description
double nextDouble()
Get the next random double.
void seed(long... seeds)
Seed the random number/vector/scenario generator to produce repeatable experiments.
• ### Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
• ### Constructor Detail

• #### ExtremeValueMC

public ExtremeValueMC(BivariateEVD bevd,
ExtremeValueMC.MarginalDistributionType marginalType)
Create an instance with a given bivariate distribution that defines the dependence structure between two consecutive simulated values, and uses UniformRNG for random number generation.
Parameters:
bevd - the dependence between two consecutive values
marginalType - the type of the marginal distribution
• #### ExtremeValueMC

public ExtremeValueMC(BivariateEVD bivariate,
ExtremeValueMC.MarginalDistributionType marginalType,
RandomNumberGenerator uniformRng)
Create an instance with a given bivariate distribution that defines the dependence structure between two consecutive simulated values, and a uniform random number generator.
Parameters:
bivariate - the dependence between two consecutive values
marginalType - the type of the marginal distribution
uniformRng - the uniform random number generator
• ### Method Detail

• #### nextDouble

public double nextDouble()
Description copied from interface: RandomNumberGenerator
Get the next random double.
Specified by:
nextDouble in interface RandomNumberGenerator
Returns:
the next random number
• #### seed

public void seed(long... seeds)
Description copied from interface: Seedable
Seed the random number/vector/scenario generator to produce repeatable experiments.
Specified by:
seed in interface Seedable
Parameters:
seeds - the seeds