Changeset 2842


Ignore:
Timestamp:
Sep 17, 2012, 6:52:20 AM (9 years ago)
Author:
Peter
Message:

remove todo doxygen tags

Location:
trunk
Files:
3 edited

Legend:

Unmodified
Added
Removed
  • trunk/build_support/yat-config.in

    r2828 r2842  
    22
    33# Copyright (C) 2008 Jari Häkkinen, Peter Johansson
    4 # Copyright (C) 2009, 2010, 2011 Peter Johansson
     4# Copyright (C) 2009, 2010, 2011, 2012 Peter Johansson
    55#
    66# This file is part of the yat library, http://dev.thep.lu.se/yat
  • trunk/yat/regression/LinearWeighted.h

    r2119 r2842  
    3535
    3636  ///
    37   /// @brief linear regression.   
     37  /// @brief linear regression.
    3838  ///
    39   /// @todo document
    40   ///
    41   class LinearWeighted : public OneDimensionalWeighted
     39  class LinearWeighted : public OneDimensionalWeighted
    4240  {
    43  
     41
    4442  public:
    4543    ///
     
    5250    ///
    5351    virtual ~LinearWeighted(void);
    54          
     52
    5553    /**
    5654       \f$ alpha \f$ is estimated as \f$ \frac{\sum w_iy_i}{\sum w_i} \f$
    57    
     55
    5856       @return the parameter \f$ \alpha \f$
    5957    */
     
    7270       \f$ beta \f$ is estimated as \f$ \frac{\sum
    7371       w_i(y_i-m_y)(x_i-m_x)}{\sum w_i(x_i-m_x)^2} \f$
    74    
     72
    7573       @return the parameter \f$ \beta \f$
    7674    */
     
    8583    */
    8684    double beta_var(void) const;
    87    
     85
    8886    /**
    8987       This function computes the best-fit linear regression
     
    9795    void fit(const utility::VectorBase& x, const utility::VectorBase& y,
    9896             const utility::VectorBase& w);
    99    
     97
    10098    ///
    101     ///  Function predicting value using the linear model: 
     99    ///  Function predicting value using the linear model:
    102100    /// \f$ y =\alpha + \beta (x - m) \f$
    103101    ///
     
    126124    double syy(void) const;
    127125    double sxy(void) const;
    128    
     126
    129127    double alpha_;
    130128    double alpha_var_;
  • trunk/yat/regression/NaiveWeighted.h

    r2119 r2842  
    3939  /// @brief naive fitting.
    4040  ///
    41   /// @todo document
    42   ///
    43   class NaiveWeighted : public OneDimensionalWeighted
     41  class NaiveWeighted : public OneDimensionalWeighted
    4442  {
    45  
     43
    4644  public:
    4745    ///
     
    5452    ///
    5553    virtual ~NaiveWeighted(void);
    56          
     54
    5755    /**
    5856       This function computes the best-fit for the naive model \f$ y
     
    6765    ///
    6866    /// Function predicting value using the naive model, i.e. a
    69     /// weighted average. 
     67    /// weighted average.
    7068    ///
    7169    double predict(const double x) const;
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