# Package org.hipparchus.optim.nonlinear.vector.leastsquares

package org.hipparchus.optim.nonlinear.vector.leastsquares

This package provides algorithms that minimize the residuals
between observations and model values.
The

Algorithms in this category need access to a

The problem can be created progressively using a

`least-squares optimizers`

minimize the distance (called
*cost*or*χ*) between model and observations.^{2}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`

.-
All Classes and Interfaces Interfaces Classes ClassDescriptionAn implementation of`LeastSquaresProblem.Evaluation`

that is designed for extension.Check if an optimization has converged based on the change in computed RMS.Gauss-Newton least-squares solver.An adapter that delegates to another implementation of`LeastSquaresProblem`

.A mutable builder for`LeastSquaresProblem`

s.A Factory for creating`LeastSquaresProblem`

s.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 a`LeastSquaresProblem`

at 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.Sequential Gauss-Newton least-squares solver.A interface for functions that compute a vector of values and can compute their derivatives (Jacobian).