LinearRegression.h

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// Copyright The OpenMS Team -- Eberhard Karls University Tuebingen,
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// $Maintainer: Timo Sachsenberg $
// $Authors: $
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#pragma once

#include <OpenMS/CONCEPT/Types.h>
#include <OpenMS/CONCEPT/Exception.h>
#include <OpenMS/DATASTRUCTURES/String.h>

#include <cmath>
#include <vector>


namespace OpenMS
{
  namespace Math
  {
    class OPENMS_DLLAPI LinearRegression
    {
public:

      LinearRegression() :
        intercept_(0),
        slope_(0),
        x_intercept_(0),
        lower_(0),
        upper_(0),
        t_star_(0),
        r_squared_(0),
        stand_dev_residuals_(0),
        mean_residuals_(0),
        stand_error_slope_(0),
        chi_squared_(0),
        rsd_(0)
      {
      }

      virtual ~LinearRegression() = default;

      void computeRegression(double confidence_interval_P,
        std::vector<double>::const_iterator x_begin,
        std::vector<double>::const_iterator x_end,
        std::vector<double>::const_iterator y_begin,
        bool compute_goodness = true);

      void computeRegressionWeighted(double confidence_interval_P, 
        std::vector<double>::const_iterator x_begin, 
        std::vector<double>::const_iterator x_end, 
        std::vector<double>::const_iterator y_begin, 
        std::vector<double>::const_iterator w_begin, 
        bool compute_goodness = true);

      double getIntercept() const;
      double getSlope() const;
      double getXIntercept() const;
      double getLower() const;
      double getUpper() const;
      double getTValue() const;
      double getRSquared() const;
      double getStandDevRes() const;
      double getMeanRes() const;
      double getStandErrSlope() const;
      double getChiSquared() const;
      double getRSD() const;

      static inline double computePointY(double x, double slope, double intercept)
      {
        return slope * x + intercept;
      }

protected:

      double intercept_;
      double slope_;
      double x_intercept_;
      double lower_;
      double upper_;
      double t_star_;
      double r_squared_;
      double stand_dev_residuals_;
      double mean_residuals_;
      double stand_error_slope_;
      double chi_squared_;
      double rsd_;

      void computeGoodness_(const std::vector<double>& X, const std::vector<double>& Y, double confidence_interval_P);

      template <typename Iterator>
      double computeChiSquare(Iterator x_begin, Iterator x_end, Iterator y_begin, double slope, double intercept);

      template <typename Iterator>
      double computeWeightedChiSquare(Iterator x_begin, Iterator x_end, Iterator y_begin, Iterator w_begin, double slope, double intercept);

private:

      LinearRegression(const LinearRegression& arg);
      LinearRegression& operator=(const LinearRegression& arg);

    }; //class

    //x, y, w must be of same size
    template <typename Iterator>
    double LinearRegression::computeChiSquare(Iterator x_begin, Iterator x_end, Iterator y_begin, double slope, double intercept)
    {
      double chi_squared = 0.0;
      Iterator xIter = x_begin;
      Iterator yIter = y_begin;
      for (; xIter != x_end; ++xIter, ++yIter)
      {
        chi_squared += std::pow(*yIter - computePointY(*xIter, slope, intercept), 2);
      }

      return chi_squared;
    }

    //x, y, w must be of same size
    template <typename Iterator>
    double LinearRegression::computeWeightedChiSquare(Iterator x_begin, Iterator x_end, Iterator y_begin, Iterator w_begin, double slope, double intercept)
    {
      double chi_squared = 0.0;
      Iterator xIter = x_begin;
      Iterator yIter = y_begin;
      Iterator wIter = w_begin;
      for (; xIter != x_end; ++xIter, ++yIter, ++wIter)
      {
        chi_squared += *wIter * std::pow(*yIter - computePointY(*xIter, slope, intercept), 2);
      }

      return chi_squared;
    }
  } // namespace Math
} // namespace OpenMS