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org.apache.commons.math3.fitting.leastsquares

public Interface LeastSquaresOptimizer

Known Direct Implementers
org.apache.commons.math3.fitting.leastsquares.LevenbergMarquardtOptimizer, org.apache.commons.math3.fitting.leastsquares.GaussNewtonOptimizer
An algorithm that can be applied to a non-linear least squares problem.
Since
3.3

Nested and Inner Type Summary

Modifier and TypeClass and Description
public static interface
LeastSquaresOptimizer.Optimum

The optimum found by the optimizer.

Method Summary

Modifier and TypeMethod and Description
public LeastSquaresOptimizer.Optimum

Returns:

The optimum.
optimize(LeastSquaresProblem
the problem definition, including model function and convergence criteria.
leastSquaresProblem)

Solve the non-linear least squares problem.

Method Detail

optimizeback to summary
public LeastSquaresOptimizer.Optimum optimize(LeastSquaresProblem leastSquaresProblem)

Solve the non-linear least squares problem.

Parameters
leastSquaresProblem:LeastSquaresProblem

the problem definition, including model function and convergence criteria.

Returns:LeastSquaresOptimizer.Optimum

The optimum.

org.apache.commons.math3.fitting.leastsquares back to summary

public Interface LeastSquaresOptimizer.Optimum

extends Evaluation
Known Direct Implementers
org.apache.commons.math3.fitting.leastsquares.OptimumImpl
The optimum found by the optimizer. This object contains the point, its value, and some metadata.

Method Summary

Modifier and TypeMethod and Description
public int

Returns:

the number of model (objective) function evaluations
getEvaluations()

Get the number of times the model was evaluated in order to produce this optimum.

public int

Returns:

the number of iterations
getIterations()

Get the number of times the algorithm iterated in order to produce this optimum.

Inherited from org.apache.commons.math3.fitting.leastsquares.LeastSquaresProblem.Evaluation:
getCostgetCovariancesgetJacobiangetPointgetResidualsgetRMSgetSigma

Method Detail

getEvaluationsback to summary
public int getEvaluations()

Get the number of times the model was evaluated in order to produce this optimum.

Returns:int

the number of model (objective) function evaluations

getIterationsback to summary
public int getIterations()

Get the number of times the algorithm iterated in order to produce this optimum. In general least squares it is common to have one evaluation per iterations.

Returns:int

the number of iterations