Package dev.nm.stat.cointegration
Class JohansenAsymptoticDistribution
- java.lang.Object
-
- dev.nm.stat.distribution.univariate.EmpiricalDistribution
-
- dev.nm.stat.cointegration.JohansenAsymptoticDistribution
-
- 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."
-
-
Nested Class Summary
Nested Classes Modifier and Type Class Description static interface
JohansenAsymptoticDistribution.F
This is a filtration function.static class
JohansenAsymptoticDistribution.Test
the available types of Johansen cointegration testsstatic class
JohansenAsymptoticDistribution.TrendType
the available types of trends
-
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.
-
-
-
Constructor Detail
-
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 biggernT
is, the finer the time discretization is, the smaller the discretization error is, and the more accurate the results are.seed
- a seed
-
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 biggernT
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 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)
-
-