com.numericalmethod.suanshu.stats.test.timeseries.adf
Class AdfAsymptoticDistribution

java.lang.Object
  com.numericalmethod.suanshu.stats.distribution.univariate.EmpiricalDistribution
      com.numericalmethod.suanshu.stats.test.timeseries.adf.AdfAsymptoticDistribution

All Implemented Interfaces:

UnivariateDistribution

public class AdfAsymptoticDistribution
extends EmpiricalDistribution

This class computes the asymptotic distribution of the augmented Dickey-Fuller (ADF) test statistics.

There are three main versions of the test and thus three possible asymptotic distributions:

1. (NO_CONSTANT) test for a unit root without drift or time trend;
2. (CONSTANT) test for a unit root with drift;
3. (CONSTANT_TIME) test for a unit root with drift and deterministic time trend.

The p-values in R are interpolated using the values from Table 4.2, p. 103 of Banerjee et al. (1993).

See Also:

• D. A. Dickey and W. A. Fuller, “Distribution of the Estimators for Autoregressive Time Series with a Unit Root,” J. Amer. Stat. Assoc., vol. 74, pp. 427–431, 1979.
• E. Said and D. A. Dickey, "Testing for Unit Roots in Autoregressive Moving Average Models of Unknown Order," Biometrika, vol. 71, 599–607, 1984.
• A. Banerjee et al., "Cointegration, Error Correction, and the Econometric Analysis of Non-Stationary Data," Oxford, Oxford University Press, 1993, ch. 4, pp. 99-135.

Field Summary

int	nSim the number of simulations
int	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.
AugmentedDickeyFuller.TrendType	trend the type of augmented Dickey-Fuller (ADF) test

Constructor Summary

AdfAsymptoticDistribution(AugmentedDickeyFuller.TrendType trend)
Construct the asymptotic distribution for the augmented Dickey-Fuller test statistics.

AdfAsymptoticDistribution(AugmentedDickeyFuller.TrendType trend, int nSim, int nT, long seed)
Construct the asymptotic distribution for the augmented Dickey-Fuller test statistics.

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

Field Detail

trend

public final AugmentedDickeyFuller.TrendType trend

the type of augmented Dickey-Fuller (ADF) test

nSim

public final int nSim

the number of simulations

nT

public final int 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.

Constructor Detail

AdfAsymptoticDistribution

public AdfAsymptoticDistribution(AugmentedDickeyFuller.TrendType trend,
                                 int nSim,
                                 int nT,
                                 long seed)

Construct the asymptotic distribution for the augmented Dickey-Fuller test statistics.

Parameters:

trend - the type of augmented Dickey-Fuller test

nSim - the number of simulations

nT - the number of grid points in interval [0, 1]

seed - the seed

AdfAsymptoticDistribution

public AdfAsymptoticDistribution(AugmentedDickeyFuller.TrendType trend)

Construct the asymptotic distribution for the augmented Dickey-Fuller test statistics.

Parameters:

trend - the type of augmented Dickey-Fuller test