Package dev.nm.stat.cointegration
Class JohansenAsymptoticDistribution
- java.lang.Object
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- dev.nm.stat.distribution.univariate.EmpiricalDistribution
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- dev.nm.stat.cointegration.JohansenAsymptoticDistribution
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- All Implemented Interfaces:
ProbabilityDistribution
public class JohansenAsymptoticDistribution extends EmpiricalDistribution
Johansen provides the asymptotic distributions of the two hypothesis testings (Eigen and Trace tests), each for 5 different trend types.- See Also:
- "Kevin Sun, Notes on Cointegration, February 23, 2011."
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Nested Class Summary
Nested Classes Modifier and Type Class Description static interfaceJohansenAsymptoticDistribution.FThis is a filtration function.static classJohansenAsymptoticDistribution.Testthe available types of Johansen cointegration testsstatic classJohansenAsymptoticDistribution.TrendTypethe available types of trends
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Constructor Summary
Constructors Constructor Description JohansenAsymptoticDistribution(JohansenAsymptoticDistribution.Test test, JohansenAsymptoticDistribution.TrendType trend, int dr)Construct the asymptotic distribution of a Johansen test.JohansenAsymptoticDistribution(JohansenAsymptoticDistribution.Test test, JohansenAsymptoticDistribution.TrendType trend, int dr, int nSim, int nT)Construct the asymptotic distribution of a Johansen test.JohansenAsymptoticDistribution(JohansenAsymptoticDistribution.Test test, JohansenAsymptoticDistribution.TrendType trend, int dr, int nSim, int nT, long seed)Construct the asymptotic distribution of a Johansen test.
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Constructor Detail
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JohansenAsymptoticDistribution
public JohansenAsymptoticDistribution(JohansenAsymptoticDistribution.Test test, JohansenAsymptoticDistribution.TrendType trend, int dr, int nSim, int nT, long seed)
Construct the asymptotic distribution of a Johansen test.- Parameters:
test- the type of Johansen cointegration testtrend- the trend typedr- the dimension of the multivariate time series (d) minus the number of cointegrating vectors (r)nSim- the number of simulationsnT- the number of grid points in interval [0, 1]. The biggernTis, the finer the time discretization is, the smaller the discretization error is, and the more accurate the results are.seed- a seed
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JohansenAsymptoticDistribution
public JohansenAsymptoticDistribution(JohansenAsymptoticDistribution.Test test, JohansenAsymptoticDistribution.TrendType trend, int dr, int nSim, int nT)
Construct the asymptotic distribution of a Johansen test.- Parameters:
test- the type of Johansen cointegration testtrend- the trend typedr- the dimension of the multivariate time series (d) minus the number of cointegrating vectors (r)nSim- the number of simulationsnT- the number of grid points in interval [0, 1]. The biggernTis, the finer the time discretization is, the smaller the discretization error is, and the more accurate the results are.
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JohansenAsymptoticDistribution
public JohansenAsymptoticDistribution(JohansenAsymptoticDistribution.Test test, JohansenAsymptoticDistribution.TrendType trend, int dr)
Construct the asymptotic distribution of a Johansen test.- Parameters:
test- the type of Johansen cointegration testtrend- the trend typedr- the dimension of the multivariate time series (d) minus the number of cointegrating vectors (r)
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