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.Evaluation
that is designed for extension.Applies a dense weight matrix to an evaluation.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 forLeastSquaresProblem
s.A Factory for creatingLeastSquaresProblem
s.A private, "field" immutable (not "real" immutable) implementation ofLeastSquaresProblem
.Container with the model lazy evaluation at a particular point.Container with the model evaluation at a particular point.Combine aMultivariateVectorFunction
with aMultivariateMatrixFunction
to produce aMultivariateJacobianFunction
.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 aLeastSquaresProblem
at a particular point.This class solves a least-squares problem using the Levenberg-Marquardt algorithm.Holds internal data.A interface for functions that compute a vector of values and can compute their derivatives (Jacobian).A pedantic implementation ofLeastSquaresOptimizer.Optimum
.Interface for validating a set of model parameters.A interface for functions that compute a vector of values and can compute their derivatives (Jacobian).