org.apache.commons.math3.fitting
Class PolynomialFitter

java.lang.Object
  org.apache.commons.math3.fitting.CurveFitter<PolynomialFunction.Parametric>
      org.apache.commons.math3.fitting.PolynomialFitter

public class PolynomialFitter
extends CurveFitter<PolynomialFunction.Parametric>

Polynomial fitting is a very simple case of curve fitting. The estimated coefficients are the polynomial coefficients (see the fit method).

Since:

2.0

Version:

$Id: PolynomialFitter.java 7721 2013-02-14 14:07:13Z CardosoP $

Constructor Summary

PolynomialFitter(MultivariateVectorOptimizer optimizer)
Simple constructor.

Method Summary

double[]	fit(double[] guess) Get the coefficients of the polynomial fitting the weighted data points.
double[]	fit(int maxEval, double[] guess) Get the coefficients of the polynomial fitting the weighted data points.

Methods inherited from class org.apache.commons.math3.fitting.CurveFitter

addObservedPoint, addObservedPoint, addObservedPoint, clearObservations, fit, fit, getObservations

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

PolynomialFitter

public PolynomialFitter(MultivariateVectorOptimizer optimizer)

Simple constructor.

Parameters:

optimizer - Optimizer to use for the fitting.

Method Detail

fit

public double[] fit(int maxEval,
                    double[] guess)

Get the coefficients of the polynomial fitting the weighted data points. The degree of the fitting polynomial is guess.length - 1.

Parameters:

guess - First guess for the coefficients. They must be sorted in increasing order of the polynomial's degree.

maxEval - Maximum number of evaluations of the polynomial.

Returns:

the coefficients of the polynomial that best fits the observed points.

Throws:

TooManyEvaluationsException - if the number of evaluations exceeds maxEval.

ConvergenceException - if the algorithm failed to converge.

fit

public double[] fit(double[] guess)

Get the coefficients of the polynomial fitting the weighted data points. The degree of the fitting polynomial is guess.length - 1.

Parameters:

guess - First guess for the coefficients. They must be sorted in increasing order of the polynomial's degree.

Returns:

the coefficients of the polynomial that best fits the observed points.

Throws:

ConvergenceException - if the algorithm failed to converge.