See: Description
| Interface | Description |
|---|---|
| LeastSquaresOptimizer |
An algorithm that can be applied to a non-linear least squares problem.
|
| LeastSquaresOptimizer.Optimum |
The optimum found by the optimizer.
|
| LeastSquaresProblem |
The data necessary to define a non-linear least squares problem.
|
| LeastSquaresProblem.Evaluation |
An evaluation of a
LeastSquaresProblem at a particular point. |
| MultivariateJacobianFunction |
A interface for functions that compute a vector of values and can compute their
derivatives (Jacobian).
|
| ParameterValidator |
Interface for validating a set of model parameters.
|
| ValueAndJacobianFunction |
A interface for functions that compute a vector of values and can compute their
derivatives (Jacobian).
|
| Class | Description |
|---|---|
| AbstractEvaluation |
An implementation of
LeastSquaresProblem.Evaluation that is designed for extension. |
| EvaluationRmsChecker |
Check if an optimization has converged based on the change in computed RMS.
|
| GaussNewtonOptimizer |
Gauss-Newton least-squares solver.
|
| LeastSquaresAdapter |
An adapter that delegates to another implementation of
LeastSquaresProblem. |
| LeastSquaresBuilder |
A mutable builder for
LeastSquaresProblems. |
| LeastSquaresFactory |
A Factory for creating
LeastSquaresProblems. |
| LevenbergMarquardtOptimizer |
This class solves a least-squares problem using the Levenberg-Marquardt
algorithm.
|
| Enum | Description |
|---|---|
| GaussNewtonOptimizer.Decomposition |
The decomposition algorithm to use to solve the normal equations.
|
least-squares optimizers minimize the distance (called
cost or χ2) between model and
observations.
LeastSquaresProblem).
Such a model predicts a set of values which the algorithm tries to match
with a set of given set of observed values.
builder or it can
be created at once using a factory.Copyright © 2003–2016 The Apache Software Foundation. All rights reserved.