MaximumLikelihoodWFunctions.h

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#ifndef MaximumLikelihoodWFunctions_h
#define MaximumLikelihoodWFunctions_h

#include <QString>

namespace Isis {
  class MaximumLikelihoodWFunctions {
  public:
    // Each model has an accompannying private method that converts from a
    // resiuduals to a weight scaler.
    enum Model {

      Huber,     
     
      HuberModified,  

      Welsch,         

      Chen
    };
    static QString modelToString(Model model);
    static MaximumLikelihoodWFunctions::Model stringToModel(QString modelName);

    MaximumLikelihoodWFunctions();
    MaximumLikelihoodWFunctions(Model modelSelection);
    MaximumLikelihoodWFunctions(Model modelSelection, double tweakingConstant);
    MaximumLikelihoodWFunctions(const MaximumLikelihoodWFunctions &other);
    ~MaximumLikelihoodWFunctions();
    MaximumLikelihoodWFunctions &operator=(const MaximumLikelihoodWFunctions &other);

    void setModel(Model modelSelection); // uses default tweaking constant
    void setTweakingConstantDefault();

    void setModel(Model modelSelection, double tweakingConstant);
    void setTweakingConstant(double tweakingConstant);

    Model model() const;
    double tweakingConstant() const;

    // the W functions provide an additional weighting factor W which is used
    // to 're-weight' each observation dynamically during an adjustment, the
    // scalar functions provide access to various flavors of this scalar (as
    // a function of the residual divided by the residuals sigma)

    double sqrtWeightScaler(double residualZScore); //it is often convient to use square roots of 
                                                    //weights when building normals, this function
                                                    // provides the scaler for the square root of
                                                    // the weight directly
    double tweakingConstantQuantile(); // returns which quantile of the residuals is recommended to
                                       // use as the tweaking constant, this varies as a function of
                                       // the model being employed

    QString weightedResidualCutoff();

    QDataStream &write(QDataStream &stream) const;
    QDataStream &read(QDataStream &stream);

  private:
    double weightScaler(double residualZScore); // This directly provides the scaler for the weight
                                                // (instead of the radical weight), thus it provides
                                                // sqrtWeightScaler^2
    double huber(double residualZScore);
    double huberModified(double residualZScore);
    double welsch(double residualZScore);
    double chen(double residualZScore);

   Model m_model; 
   double m_tweakingConstant; 
 };
  // operators to read/write to/from binary data
  QDataStream &operator<<(QDataStream &stream, const MaximumLikelihoodWFunctions &mlwf);
  QDataStream &operator>>(QDataStream &stream, MaximumLikelihoodWFunctions &mlwf);

  QDataStream &operator<<(QDataStream &stream, const MaximumLikelihoodWFunctions::Model &modelEnum);
  QDataStream &operator>>(QDataStream &stream, MaximumLikelihoodWFunctions::Model &modelEnum);

};// end namespace Isis

#endif