/** * Creates a new instance of Statistic * @param targets * Collection of ground-truth targets for the learned approximator * @param estimates * Collection of estimates from the learned approximator * @param numParameters * Number of parameters in the learned approximator */ public Statistic( Collection<Double> targets, Collection<Double> estimates, int numParameters ) { super( 0.0 ); Collection<Double> weights = Collections.nCopies( targets.size(), new Double( 1.0 ) ); this.computeStatistics( targets, estimates, weights, numParameters ); }
/** * Creates a new instance of Statistic * @param targets * Collection of ground-truth targets for the learned approximator * @param estimates * Collection of estimates from the learned approximator * @param weights * Collection of weights to apply to the corresponding target-estimate * pair * @param numParameters * Number of parameters in the learned approximator */ public Statistic( Collection<Double> targets, Collection<Double> estimates, Collection<Double> weights, int numParameters ) { super( 0.0 ); this.computeStatistics( targets, estimates, weights, numParameters ); }
/** * Creates a new instance of Statistic * @param targets * Collection of ground-truth targets for the learned approximator * @param estimates * Collection of estimates from the learned approximator * @param weights * Collection of weights to apply to the corresponding target-estimate * pair * @param numParameters * Number of parameters in the learned approximator */ public Statistic( Collection<Double> targets, Collection<Double> estimates, Collection<Double> weights, int numParameters ) { super( 0.0 ); this.computeStatistics( targets, estimates, weights, numParameters ); }
/** * Creates a new instance of Statistic * @param targets * Collection of ground-truth targets for the learned approximator * @param estimates * Collection of estimates from the learned approximator * @param weights * Collection of weights to apply to the corresponding target-estimate * pair * @param numParameters * Number of parameters in the learned approximator */ public Statistic( Collection<Double> targets, Collection<Double> estimates, Collection<Double> weights, int numParameters ) { super( 0.0 ); this.computeStatistics( targets, estimates, weights, numParameters ); }
/** * Creates a new instance of Statistic * @param targets * Collection of ground-truth targets for the learned approximator * @param estimates * Collection of estimates from the learned approximator * @param numParameters * Number of parameters in the learned approximator */ public Statistic( Collection<Double> targets, Collection<Double> estimates, int numParameters ) { super( 0.0 ); Collection<Double> weights = Collections.nCopies( targets.size(), new Double( 1.0 ) ); this.computeStatistics( targets, estimates, weights, numParameters ); }
/** * Creates a new instance of Statistic * @param targets * Collection of ground-truth targets for the learned approximator * @param estimates * Collection of estimates from the learned approximator * @param numParameters * Number of parameters in the learned approximator */ public Statistic( Collection<Double> targets, Collection<Double> estimates, int numParameters ) { super( 0.0 ); Collection<Double> weights = Collections.nCopies( targets.size(), new Double( 1.0 ) ); this.computeStatistics( targets, estimates, weights, numParameters ); }
/** * Copy Constructor * @param other * Statistic to copy */ private Statistic( Statistic other ) { super( other.getNullHypothesisProbability() ); this.setDegreesOfFreedom( other.getDegreesOfFreedom() ); this.setMeanL1Error( other.getMeanL1Error() ); this.setNumParameters( other.getNumParameters() ); this.setNumSamples( other.getNumSamples() ); this.setRootMeanSquaredError( other.getRootMeanSquaredError() ); this.setTargetEstimateCorrelation( other.getTargetEstimateCorrelation() ); this.setUnpredictedErrorFraction( other.getUnpredictedErrorFraction() ); }
/** * Copy Constructor * @param other * Statistic to copy */ private Statistic( Statistic other ) { super( other.getNullHypothesisProbability() ); this.setDegreesOfFreedom( other.getDegreesOfFreedom() ); this.setMeanL1Error( other.getMeanL1Error() ); this.setNumParameters( other.getNumParameters() ); this.setNumSamples( other.getNumSamples() ); this.setRootMeanSquaredError( other.getRootMeanSquaredError() ); this.setTargetEstimateCorrelation( other.getTargetEstimateCorrelation() ); this.setUnpredictedErrorFraction( other.getUnpredictedErrorFraction() ); }
/** * Copy Constructor * @param other * Statistic to copy */ private Statistic( Statistic other ) { super( other.getNullHypothesisProbability() ); this.setDegreesOfFreedom( other.getDegreesOfFreedom() ); this.setMeanL1Error( other.getMeanL1Error() ); this.setNumParameters( other.getNumParameters() ); this.setNumSamples( other.getNumSamples() ); this.setRootMeanSquaredError( other.getRootMeanSquaredError() ); this.setTargetEstimateCorrelation( other.getTargetEstimateCorrelation() ); this.setUnpredictedErrorFraction( other.getUnpredictedErrorFraction() ); }
@Override public double getTestStatistic() { return this.getChiSquare(); }
@Override public double getTestStatistic() { return this.getChiSquare(); }
@Override public double getTestStatistic() { return this.getChiSquare(); }