org.apache.commons.math3.optimization.fitting

## Class PolynomialFitter

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

- Deprecated.
  As of 3.1 (to be removed in 4.0).

      @Deprecated
      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

- - ### Constructor Summary

    Constructors
    Constructor and Description
    `PolynomialFitter(DifferentiableMultivariateVectorOptimizer optimizer)` Deprecated. Simple constructor.
    `PolynomialFitter(int degree, DifferentiableMultivariateVectorOptimizer optimizer)` Deprecated. Since 3.1 (to be removed in 4.0). Please use `PolynomialFitter(DifferentiableMultivariateVectorOptimizer)` instead.

  - ### Method Summary

    Methods
    Modifier and Type | Method and Description
    --- | ---
    `double[]` | `fit()` Deprecated. Since 3.1 (to be removed in 4.0). Please use `fit(double[])` instead.
    `double[]` | `fit(double[] guess)` Deprecated. Get the coefficients of the polynomial fitting the weighted data points.
    `double[]` | `fit(int maxEval, double[] guess)` Deprecated. Get the coefficients of the polynomial fitting the weighted data points.

    - ### Methods inherited from class org.apache.commons.math3.optimization.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

          @Deprecated
          public PolynomialFitter(int degree,
                                     DifferentiableMultivariateVectorOptimizer optimizer)

      Deprecated. Since 3.1 (to be removed in 4.0). Please use `PolynomialFitter(DifferentiableMultivariateVectorOptimizer)` instead.
      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.

    - #### PolynomialFitter

          public PolynomialFitter(DifferentiableMultivariateVectorOptimizer optimizer)

      Deprecated.
      Simple constructor.
      Parameters:
        `optimizer` - Optimizer to use for the fitting.
      Since:
        3.1

  - ### Method Detail

    - #### fit

          @Deprecated
          public double[] fit()

      Deprecated. Since 3.1 (to be removed in 4.0). Please use `fit(double[])` instead.
      Get the polynomial fitting the weighted (x, y) points.
      Returns:
        the coefficients of the polynomial that best fits the observed points.
      Throws:
        `ConvergenceException` - if the algorithm failed to converge.

    - #### fit

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

      Deprecated.
      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.
      Since:
        3.1

    - #### fit

          public double[] fit(double[] guess)

      Deprecated.
      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.
      Since:
        3.1

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