org.apache.commons.math3.fitting.leastsquares

## Class EvaluationRmsChecker

- java.lang.Object
- - org.apache.commons.math3.fitting.leastsquares.EvaluationRmsChecker

- All Implemented Interfaces:
    ConvergenceChecker<LeastSquaresProblem.Evaluation>

      public class EvaluationRmsChecker
      extends Object
      implements ConvergenceChecker<LeastSquaresProblem.Evaluation>

  Check if an optimization has converged based on the change in computed RMS.
  Since:
    3.4

- - ### Constructor Summary

    Constructors
    Constructor and Description
    `EvaluationRmsChecker(double tol)` Create a convergence checker for the RMS with the same relative and absolute tolerance.
    `EvaluationRmsChecker(double relTol, double absTol)` Create a convergence checker for the RMS with a relative and absolute tolerance.

  - ### Method Summary

    Methods
    Modifier and Type | Method and Description
    --- | ---
    `boolean` | `converged(int iteration, LeastSquaresProblem.Evaluation previous, LeastSquaresProblem.Evaluation current)` Check if the optimization algorithm has converged.

    - ### Methods inherited from class java.lang.Object

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

- - ### Constructor Detail

    - #### EvaluationRmsChecker

          public EvaluationRmsChecker(double tol)

      Create a convergence checker for the RMS with the same relative and absolute tolerance.

      Convenience constructor for when the relative and absolute tolerances are the same. Same as `new EvaluationRmsChecker(tol, tol)`.

      Parameters:
        `tol` - the relative and absolute tolerance.
      See Also:
        `EvaluationRmsChecker(double, double)`

    - #### EvaluationRmsChecker

          public EvaluationRmsChecker(double relTol,
                              double absTol)

      Create a convergence checker for the RMS with a relative and absolute tolerance.

      The optimization has converged when the RMS of consecutive evaluations are equal to within the given relative tolerance or absolute tolerance.

      Parameters:
        `relTol` - the relative tolerance.
        `absTol` - the absolute tolerance.
      See Also:
        `Precision.equals(double, double, double)`, `Precision.equalsWithRelativeTolerance(double, double, double)`

  - ### Method Detail

    - #### converged

          public boolean converged(int iteration,
                          LeastSquaresProblem.Evaluation previous,
                          LeastSquaresProblem.Evaluation current)

      Check if the optimization algorithm has converged.
      Specified by:
        `converged` in interface `ConvergenceChecker<LeastSquaresProblem.Evaluation>`
      Parameters:
        `iteration` - Current iteration.
        `previous` - Best point in the previous iteration.
        `current` - Best point in the current iteration.
      Returns:
        `true` if the algorithm is considered to have converged.

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