org.codehaus.jet.hypothesis.rejection.estimators
Class CriticalValueEstimator
java.lang.Object
org.codehaus.jet.hypothesis.rejection.estimators.AbstractRejectionValueEstimator
org.codehaus.jet.hypothesis.rejection.estimators.CriticalValueEstimator
- All Implemented Interfaces:
- RejectionValueEstimator
public class CriticalValueEstimator
- extends AbstractRejectionValueEstimator
Estimator of critical value for unit roots and cointegration tests.
- Author:
- Mauro Talevi
- See Also:
RejectionValueEstimator
Method Summary |
double |
estimateAsymptoticValue(double[] norms,
double[] probs,
double[] weights,
double[] criticalValues,
double level)
Estimates an asymptotic rejection value |
double |
estimateValue(double[] norms,
double[] probs,
double[] weights,
double[][] beta,
int sampleSize,
int[] params,
double level)
Estimates a rejection value |
protected double[] |
toMiddleYSample(double[][] beta,
int min,
int np,
int sampleSize,
int[] params)
|
protected double[] |
toTailYSample(double[][] beta,
int min,
int np,
int sampleSize,
int[] params,
boolean upper)
|
protected double[] |
toYSample(double[][] beta,
int min,
int np,
int sampleSize,
int[] params)
|
Methods inherited from class org.codehaus.jet.hypothesis.rejection.estimators.AbstractRejectionValueEstimator |
calculateMinimizingIndex, cumulativeNormal, extractMiddleColumnPoints, extractTailColumnPoints, getNumberOfPoints, getTailPoints, getThreshold, glsRegression, inverseCumulativeNormal, isLower, isMiddle, powerSeries, toCovariance, toCriticalValues, toMiddleCovariance, toMiddleIndex, toMiddleXSample, toMiddleYSample, toTailCovariance, toTailXSample, toTailYSample, toUpperIndex, toXSample, toYSample, tTest, validateParams |
Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
CriticalValueEstimator
public CriticalValueEstimator(int numberOfPoints,
double threshold)
- Creates a CriticalValueEstimator
- Parameters:
numberOfPoints
- the number of points used in the regressionthreshold
- the threshold used for the t-test
CriticalValueEstimator
public CriticalValueEstimator(ResponseSurfaceEvaluator responseSurfaceEvaluator,
int numberOfPoints,
double threshold)
- Creates a CriticalValueEstimator
- Parameters:
responseSurfaceEvaluator
- the ResponseSurfaceEvaluatornumberOfPoints
- the number of points used in the regressionthreshold
- the threshold used for the t-test
estimateValue
public double estimateValue(double[] norms,
double[] probs,
double[] weights,
double[][] beta,
int sampleSize,
int[] params,
double level)
- Description copied from interface:
RejectionValueEstimator
- Estimates a rejection value
- Parameters:
norms
- the normalisations used to construct the regressors matrixprobs
- the probabilities used to construct the covariance matrixweights
- the weights sed to construct the covariance matrixbeta
- the beta valuessampleSize
- the sample sizeparams
- the params specific to different testslevel
- the significance level
- Returns:
- A rejection value
estimateAsymptoticValue
public double estimateAsymptoticValue(double[] norms,
double[] probs,
double[] weights,
double[] criticalValues,
double level)
- Description copied from interface:
RejectionValueEstimator
- Estimates an asymptotic rejection value
- Parameters:
norms
- the normalisations used to construct the regressors matrixprobs
- the probabilities used to construct the covariance matrixweights
- the weights used to construct the covariance matrixcriticalValues
- the criticalvalueslevel
- the significance level
- Returns:
- A rejection value
toYSample
protected double[] toYSample(double[][] beta,
int min,
int np,
int sampleSize,
int[] params)
toMiddleYSample
protected double[] toMiddleYSample(double[][] beta,
int min,
int np,
int sampleSize,
int[] params)
toTailYSample
protected double[] toTailYSample(double[][] beta,
int min,
int np,
int sampleSize,
int[] params,
boolean upper)
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