Ignore:
Timestamp:
Dec 21, 2006, 3:43:31 PM (15 years ago)
Author:
Peter
Message:

Fixes #77, #78, #158, and #163, and refs #81

File:
1 edited

Legend:

Unmodified
Added
Removed
  • trunk/yat/regression/Naive.h

    r703 r713  
    3737namespace regression {
    3838
    39   ///
    40   /// @bief naive fitting.
    41   ///
    42   /// @todo document
    43   ///
     39  /**
     40     @brief Naive Regression
     41   
     42     Data are modeled as \f$ y_i = \alpha + \epsilon_i \f$
     43
     44  */
    4445  class Naive : public OneDimensional
    4546  {
     
    5657    virtual ~Naive(void);
    5758         
     59    /**
     60        \f$\frac{1}{N-1} \sum (x_i-m)^2 \f$
     61   
     62        @brief Mean Squared Error
     63    */
     64    double chisq(void) const;
     65
    5866    ///
    5967    /// This function computes the best-fit for the naive model \f$ y
    6068    /// = m \f$ from vectors \a x and \a y, by minimizing \f$
    61     /// \sum{(y_i-m)^2} \f$. This function is the same as using the
    62     /// weighted version with unity weights.
     69    /// \sum{(y_i-m)^2} \f$.
    6370    ///
    6471    void fit(const utility::vector& x, const utility::vector& y);
    6572
    6673    ///
    67     /// @brief Mean Squared Error
    68     ///
    69     inline double mse(void) const { return mse_; }
    70 
    71     ///
    72     /// Function predicting value using the naive model.
     74    /// The predicted value is the average \f$ m \f$
    7375    ///
    7476    double predict(const double x) const;
     
    7678    ///
    7779    /// @return standard error
     80    ///
     81    /// @see statistics::Averager
    7882    ///
    7983    double standard_error(const double x) const;
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