Package org.apache.commons.math3.fitting.leastsquares
package org.apache.commons.math3.fitting.leastsquares
This package provides algorithms that minimize the residuals
between observations and model values.
The
Algorithms in this category need access to a problem (represented by a
The problem can be created progressively using a
least-squares optimizers minimize the distance (called
cost or χ2) between model and
observations.
Algorithms in this category need access to a problem (represented by a
LeastSquaresProblem).
Such a model predicts a set of values which the algorithm tries to match
with a set of given set of observed values.
The problem can be created progressively using a
builder or it can
be created at once using a factory.- Since:
- 3.3
-
ClassDescriptionAn implementation of
LeastSquaresProblem.Evaluationthat is designed for extension.Check if an optimization has converged based on the change in computed RMS.Gauss-Newton least-squares solver.The decomposition algorithm to use to solve the normal equations.An adapter that delegates to another implementation ofLeastSquaresProblem.A mutable builder forLeastSquaresProblems.A Factory for creatingLeastSquaresProblems.An algorithm that can be applied to a non-linear least squares problem.The optimum found by the optimizer.The data necessary to define a non-linear least squares problem.An evaluation of aLeastSquaresProblemat a particular point.This class solves a least-squares problem using the Levenberg-Marquardt algorithm.A interface for functions that compute a vector of values and can compute their derivatives (Jacobian).Interface for validating a set of model parameters.A interface for functions that compute a vector of values and can compute their derivatives (Jacobian).