Changeset 429 for trunk/lib/statistics/Naive.h

Timestamp:

Dec 8, 2005, 8:50:11 PM (18 years ago)

Author:

Peter

Message:

separating weighted and non-weighted regression to different classes.

File:

• trunk/lib/statistics/Naive.h (modified) (2 diffs)

trunk/lib/statistics/Naive.h

@@ -7 +7 @@
 
 #include <c++_tools/gslapi/vector.h>
-#include <c++_tools/statistics/Averager.h>
-#include <c++_tools/statistics/AveragerWeighted.h>
 
 #include <iostream>
@@ -51 +49 @@
 
     ///
-    /// This function computes the best-fit for the naive model \f$ y
-    /// = m \f$ from vectors \a x and \a y, by minimizing \f$ \sum
-    /// w_i(y_i-m)^2 \f$. The weight \f$ w_i \f$ is proportional to
-    /// the inverse of the variance for \f$ y_i \f$
-    ///
-    void fit(const gslapi::vector& x,
-             const gslapi::vector& y,
-             const gslapi::vector& w);
-
-    ///
     /// Function predicting value using the naive model. \a y_err is
     /// the expected deviation from the line for a new data point. The
-    /// weight for the new point can be specified. A smaller weight
-    /// means larger error. The error has two components: the variance
-    /// of point and error in estimation of m_.
+    /// error has two components: the variance of point and error in
+    /// estimation of the mean.
     ///
-    void predict(const double x, double& y, double& y_err, 
-                 const double w=1) ;
+    void predict(const double x, double& y, double& y_err) ;
 
-    ///
-    /// @return prediction value and parameters
-    ///
-    std::ostream& print(std::ostream&) const;
-             
     ///
     /// @return header for print()