MaximumLikelihoodWFunctions.h

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#ifndef MaximumLikelihoodWFunctions_h
#define MaximumLikelihoodWFunctions_h

namespace Isis {
  class MaximumLikelihoodWFunctions {
  public:
    enum Model {

      Huber,     
     
      HuberModified,  

      Welsch,         

      Chen            
    };

    MaximumLikelihoodWFunctions() {this->setModel(Huber);}; //choose Model and define the tweaking constant
    MaximumLikelihoodWFunctions(Model modelSelection, double tweakingConstant); //choose Model and define the tweaking constant
    MaximumLikelihoodWFunctions(Model modelSelection);                          //choose Model and and use the default tweaking constant
    ~MaximumLikelihoodWFunctions() {}; //empty destructor
  
    bool setModel(Model modelSelection, double tweakingConstant); //choose Model and define the tweaking constant
    bool setModel(Model modelSelection);  //choose Model and use default tweaking constant
    bool setTweakingConstant(double tweakingConstant); //leave model type unaltered and change tweaking constant
    bool setTweakingConstantDefault();  //reset tweaking constant to the default for the current model

    //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

    double tweakingConstant();

    void maximumLikelihoodModel(char *model);
 
    void weightedResidualCutoff(char *cutoff);

  private:
    double m_c;    //the tweaking constant for the maximum likelihood models

    double m_PI;   //PI

    Model m_model; //selected maximum likelihood estimation model


    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);
  };
}// end namespace Isis

#endif