Last change
on this file since 429 was
429,
checked in by Peter, 16 years ago

separating weighted and nonweighted regression to different classes.


Property svn:eolstyle set to
native

Property svn:keywords set to
Author Date Id Revision

File size:
1.4 KB

Line  

1  // $Id: OneDimensional.h 429 20051208 19:50:11Z peter $ 

2  

3  #ifndef _theplu_statistics_regression_onedimensioanl_ 

4  #define _theplu_statistics_regression_onedimensioanl_ 

5  

6  #include <c++_tools/statistics/AveragerPair.h> 

7  

8  #include <ostream> 

9  

10  namespace theplu { 

11  namespace gslapi { 

12  class vector; 

13  } 

14  

15  namespace statistics { 

16  namespace regression { 

17  

18  /// 

19  /// Abstract Base Class for One Dimensional fitting. 

20  /// 

21  /// @todo document 

22  /// 

23  class OneDimensional 

24  { 

25  

26  public: 

27  /// 

28  /// Default Constructor. 

29  /// 

30  inline OneDimensional(void) {} 

31  

32  /// 

33  /// Destructor 

34  /// 

35  virtual ~OneDimensional(void) {}; 

36  

37  /// 

38  /// This function computes the bestfit given a model (see 

39  /// specific class for details) by minimizing \f$ 

40  /// \sum{(\hat{y_i}y_i)^2} \f$, where \f$ \hat{y} \f$ is the fitted value. 

41  /// 

42  virtual void fit(const gslapi::vector& x, const gslapi::vector& y)=0; 

43  

44  /// 

45  /// function predicting in one point 

46  /// 

47  virtual void predict(const double x, double& y, double& y_err) const=0; 

48  

49  /// 

50  /// 

51  /// 

52  /// @return stream of prediction values and parameters 

53  /// 

54  std::ostream& print(std::ostream&,const double min, 

55  const double max, const u_int n) const; 

56  

57  /// 

58  /// @return header for print() 

59  /// 

60  virtual std::ostream& print_header(std::ostream& s) const=0; 

61  

62  protected: 

63  /// 

64  /// Averager for pair of x and y 

65  /// 

66  AveragerPair ap_; 

67  

68  }; 

69  

70  }}} // of namespaces regression, statisitcs and thep 

71  

72  #endif 

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