com.numericalmethod.suanshu.stats.cointegration
Class JohansenAsymptoticDistribution

java.lang.Object
  com.numericalmethod.suanshu.stats.distribution.univariate.EmpiricalDistribution
      com.numericalmethod.suanshu.stats.cointegration.JohansenAsymptoticDistribution

All Implemented Interfaces:

UnivariateDistribution

public class JohansenAsymptoticDistribution
extends EmpiricalDistribution

This class represents the asymptotic distribution of Johansen's tests JohansenAsymptoticDistribution.Test for 5 different cases. They are JohansenAsymptoticDistribution.TrendType.

Nested Class Summary

static class	JohansenAsymptoticDistribution.Test the types of Johansen's cointegration tests available
static class	JohansenAsymptoticDistribution.TrendType the types of trends available

Constructor Summary

JohansenAsymptoticDistribution(JohansenAsymptoticDistribution.Test test, JohansenAsymptoticDistribution.TrendType trend, int dr)
Construct the asymptotic distribution for Johansen's tests.

JohansenAsymptoticDistribution(JohansenAsymptoticDistribution.Test test, JohansenAsymptoticDistribution.TrendType trend, int dr, long seed, int nSim, int nT)
Construct the asymptotic distribution for Johansen's tests.

Method Summary

Methods inherited from class com.numericalmethod.suanshu.stats.distribution.univariate.EmpiricalDistribution

cdf, density, entropy, kurtosis, mean, median, moment, quantile, skew, variance

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

JohansenAsymptoticDistribution

public JohansenAsymptoticDistribution(JohansenAsymptoticDistribution.Test test,
                                      JohansenAsymptoticDistribution.TrendType trend,
                                      int dr,
                                      long seed,
                                      int nSim,
                                      int nT)

Construct the asymptotic distribution for Johansen's tests.

Parameters:

test - the type of Johansen's cointegration test

trend - the trend type

dr - the dimension of the multivariate time series (d) minus the number of cointegrating vectors (r)

nSim - the number of simulations

nT - the number of grid points in interval [0, 1]; the bigger nT is, the finer the time discretization is, the smaller the discretization error is, and the more accurate the results are.

JohansenAsymptoticDistribution

public JohansenAsymptoticDistribution(JohansenAsymptoticDistribution.Test test,
                                      JohansenAsymptoticDistribution.TrendType trend,
                                      int dr)

Construct the asymptotic distribution for Johansen's tests.

Parameters:

test - the type of Johansen's cointegration test

trend - the trend type

dr - the dimension of the multivariate time series (d) minus the number of cointegrating vectors (r)