org.codehaus.jet.hypothesis.rejection.estimators
Class AbstractRejectionValueEstimator

java.lang.Object
  extended by org.codehaus.jet.hypothesis.rejection.estimators.AbstractRejectionValueEstimator
All Implemented Interfaces:
RejectionValueEstimator
Direct Known Subclasses:
CriticalValueEstimator, PValueEstimator

public abstract class AbstractRejectionValueEstimator
extends java.lang.Object
implements RejectionValueEstimator

Abstract base RejectionValueEstimator. Concrete implementations include the CriticalValueEstimator and PValueEstimator.

Author:
Mauro Talevi
See Also:
CriticalValueEstimator, PValueEstimator

Field Summary
protected  org.apache.commons.math.distribution.NormalDistribution distribution
           
protected  org.codehaus.jet.regression.MultipleLinearRegressionEstimator gls
           
protected  ResponseSurfaceEvaluator responseSurfaceEvaluator
           
 
Constructor Summary
AbstractRejectionValueEstimator(int numberOfPoints, double threshold)
          Creates an AbstractRejectionValueEstimator
AbstractRejectionValueEstimator(ResponseSurfaceEvaluator responseSurfaceEvaluator, int numberOfPoints, double threshold)
           
 
Method Summary
protected  int calculateMinimizingIndex(double[] values, double level, double threshold)
           
protected  double cumulativeNormal(double level)
           
protected  double[] extractMiddleColumnPoints(double[][] beta, int first, int min, int np)
           
protected  double[] extractTailColumnPoints(double[][] beta, int first, int np, boolean upper)
           
protected  int getNumberOfPoints()
           
protected  int getTailPoints(int min, int np, boolean upper)
           
protected  double getThreshold()
           
protected  double[] glsRegression(double[] y, double[][] x, double[][] omega)
           
protected  double inverseCumulativeNormal(double level)
           
protected  boolean isLower(int min, int np)
           
protected  boolean isMiddle(int min, int np)
           
protected  double powerSeries(double[] series, double x, int order)
           
protected  double[][] toCovariance(double[] probs, double[] weights, int min, int np)
           
protected  double[] toCriticalValues(double[][] beta, int sampleSize, int[] params)
           
protected  double[][] toMiddleCovariance(double[] probs, double[] weights, int min, int np)
           
protected  int toMiddleIndex(int min, int np, int i)
           
protected  double[][] toMiddleXSample(double[] values, int min, int np, int nvar)
           
protected  double[] toMiddleYSample(double[] values, int min, int np)
           
protected  double[][] toTailCovariance(double[] probs, double[] weights, int np, boolean upper)
           
protected  double[][] toTailXSample(double[] values, int np, int nvar, boolean upper)
           
protected  double[] toTailYSample(double[] values, int np, boolean upper)
           
protected  int toUpperIndex(int i)
           
protected  double[][] toXSample(double[] norms, int min, int np, int nvar)
           
protected  double[] toYSample(double[] values, int min, int np)
           
protected  boolean tTest(double[] gamma, int element, double threshold)
           
protected  void validateParams(int sampleSize, double level)
           
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 
Methods inherited from interface org.codehaus.jet.hypothesis.rejection.RejectionValueEstimator
estimateAsymptoticValue, estimateValue
 

Field Detail

distribution

protected org.apache.commons.math.distribution.NormalDistribution distribution

gls

protected org.codehaus.jet.regression.MultipleLinearRegressionEstimator gls

responseSurfaceEvaluator

protected ResponseSurfaceEvaluator responseSurfaceEvaluator
Constructor Detail

AbstractRejectionValueEstimator

public AbstractRejectionValueEstimator(int numberOfPoints,
                                       double threshold)
Creates an AbstractRejectionValueEstimator

Parameters:
numberOfPoints -
threshold -

AbstractRejectionValueEstimator

public AbstractRejectionValueEstimator(ResponseSurfaceEvaluator responseSurfaceEvaluator,
                                       int numberOfPoints,
                                       double threshold)
Parameters:
responseSurfaceEvaluator -
numberOfPoints -
threshold -
Method Detail

validateParams

protected void validateParams(int sampleSize,
                              double level)

powerSeries

protected double powerSeries(double[] series,
                             double x,
                             int order)

calculateMinimizingIndex

protected int calculateMinimizingIndex(double[] values,
                                       double level,
                                       double threshold)

extractMiddleColumnPoints

protected double[] extractMiddleColumnPoints(double[][] beta,
                                             int first,
                                             int min,
                                             int np)

extractTailColumnPoints

protected double[] extractTailColumnPoints(double[][] beta,
                                           int first,
                                           int np,
                                           boolean upper)

isMiddle

protected boolean isMiddle(int min,
                           int np)

isLower

protected boolean isLower(int min,
                          int np)

toMiddleIndex

protected int toMiddleIndex(int min,
                            int np,
                            int i)

toUpperIndex

protected int toUpperIndex(int i)

getTailPoints

protected int getTailPoints(int min,
                            int np,
                            boolean upper)

toXSample

protected double[][] toXSample(double[] norms,
                               int min,
                               int np,
                               int nvar)

toMiddleXSample

protected double[][] toMiddleXSample(double[] values,
                                     int min,
                                     int np,
                                     int nvar)

toTailXSample

protected double[][] toTailXSample(double[] values,
                                   int np,
                                   int nvar,
                                   boolean upper)

toCovariance

protected double[][] toCovariance(double[] probs,
                                  double[] weights,
                                  int min,
                                  int np)

toMiddleCovariance

protected double[][] toMiddleCovariance(double[] probs,
                                        double[] weights,
                                        int min,
                                        int np)

toTailCovariance

protected double[][] toTailCovariance(double[] probs,
                                      double[] weights,
                                      int np,
                                      boolean upper)

toCriticalValues

protected double[] toCriticalValues(double[][] beta,
                                    int sampleSize,
                                    int[] params)

glsRegression

protected double[] glsRegression(double[] y,
                                 double[][] x,
                                 double[][] omega)

tTest

protected boolean tTest(double[] gamma,
                        int element,
                        double threshold)

cumulativeNormal

protected double cumulativeNormal(double level)

inverseCumulativeNormal

protected double inverseCumulativeNormal(double level)

getNumberOfPoints

protected int getNumberOfPoints()

getThreshold

protected double getThreshold()

toYSample

protected double[] toYSample(double[] values,
                             int min,
                             int np)

toMiddleYSample

protected double[] toMiddleYSample(double[] values,
                                   int min,
                                   int np)

toTailYSample

protected double[] toTailYSample(double[] values,
                                 int np,
                                 boolean upper)


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