PolynomialFitter (Commons Math 2.2 API)

java.lang.Object
- org.apache.commons.math.optimization.fitting.PolynomialFitter

```
public class PolynomialFitter
extends java.lang.Object
```
This class implements a curve fitting specialized for polynomials.
Polynomial fitting is a very simple case of curve fitting. The estimated coefficients are the polynomial coefficients. They are searched by a least square estimator.

Since:

2.0

Version:

$Revision: 1073270 $ $Date: 2011-02-22 10:19:27 +0100 (mar. 22 févr. 2011) $

Constructor Summary

Constructors
Constructor Description

PolynomialFitter(int degree, DifferentiableMultivariateVectorialOptimizer optimizer)
Simple constructor.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`void`	`addObservedPoint(double weight, double x, double y)`	Add an observed weighted (x,y) point to the sample.
`void`	`clearObservations()`	Remove all observations.
`PolynomialFunction`	`fit()`	Get the polynomial fitting the weighted (x, y) points.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Constructor Detail
  - PolynomialFitter
```
public PolynomialFitter(int degree,
                        DifferentiableMultivariateVectorialOptimizer optimizer)
```
    Simple constructor.
    The polynomial fitter built this way are complete polynomials, ie. a n-degree polynomial has n+1 coefficients.
    
    Parameters:
    
    degree - maximal degree of the polynomial
    
    optimizer - optimizer to use for the fitting
- Method Detail
  - addObservedPoint
```
public void addObservedPoint(double weight,
                             double x,
                             double y)
```
    Add an observed weighted (x,y) point to the sample.
    
    Parameters:
    
    weight - weight of the observed point in the fit
    
    x - abscissa of the point
    
    y - observed value of the point at x, after fitting we should have P(x) as close as possible to this value
  - clearObservations
```
public void clearObservations()
```
    Remove all observations.
    
    Since:
    
    2.2
  - fit
```
public PolynomialFunction fit()
                       throws OptimizationException
```
    Get the polynomial fitting the weighted (x, y) points.
    
    Returns:
    
    polynomial function best fitting the observed points
    
    Throws:
    
    OptimizationException - if the algorithm failed to converge