Package | Description |
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org.hipparchus.fitting |
Classes to perform curve fitting.
|
org.hipparchus.optim.nonlinear.vector.leastsquares |
This package provides algorithms that minimize the residuals
between observations and model values.
|
Modifier and Type | Method and Description |
---|---|
protected LeastSquaresProblem |
HarmonicCurveFitter.getProblem(Collection<WeightedObservedPoint> observations)
Creates a least squares problem corresponding to the appropriate curve.
|
protected LeastSquaresProblem |
PolynomialCurveFitter.getProblem(Collection<WeightedObservedPoint> observations)
Creates a least squares problem corresponding to the appropriate curve.
|
protected abstract LeastSquaresProblem |
AbstractCurveFitter.getProblem(Collection<WeightedObservedPoint> points)
Creates a least squares problem corresponding to the appropriate curve.
|
protected LeastSquaresProblem |
GaussianCurveFitter.getProblem(Collection<WeightedObservedPoint> observations)
Creates a least squares problem corresponding to the appropriate curve.
|
protected LeastSquaresProblem |
SimpleCurveFitter.getProblem(Collection<WeightedObservedPoint> observations)
Creates a least squares problem corresponding to the appropriate curve.
|
Modifier and Type | Class and Description |
---|---|
class |
LeastSquaresAdapter
An adapter that delegates to another implementation of
LeastSquaresProblem . |
Modifier and Type | Method and Description |
---|---|
LeastSquaresProblem |
LeastSquaresBuilder.build()
Construct a
LeastSquaresProblem from the data in this builder. |
static LeastSquaresProblem |
LeastSquaresFactory.countEvaluations(LeastSquaresProblem problem,
Incrementor counter)
Count the evaluations of a particular problem.
|
static LeastSquaresProblem |
LeastSquaresFactory.create(MultivariateJacobianFunction model,
RealVector observed,
RealVector start,
ConvergenceChecker<LeastSquaresProblem.Evaluation> checker,
int maxEvaluations,
int maxIterations)
Create a
LeastSquaresProblem
from the given elements. |
static LeastSquaresProblem |
LeastSquaresFactory.create(MultivariateJacobianFunction model,
RealVector observed,
RealVector start,
RealMatrix weight,
ConvergenceChecker<LeastSquaresProblem.Evaluation> checker,
int maxEvaluations,
int maxIterations)
Create a
LeastSquaresProblem
from the given elements. |
static LeastSquaresProblem |
LeastSquaresFactory.create(MultivariateJacobianFunction model,
RealVector observed,
RealVector start,
RealMatrix weight,
ConvergenceChecker<LeastSquaresProblem.Evaluation> checker,
int maxEvaluations,
int maxIterations,
boolean lazyEvaluation,
ParameterValidator paramValidator)
Create a
LeastSquaresProblem
from the given elements. |
static LeastSquaresProblem |
LeastSquaresFactory.create(MultivariateVectorFunction model,
MultivariateMatrixFunction jacobian,
double[] observed,
double[] start,
RealMatrix weight,
ConvergenceChecker<LeastSquaresProblem.Evaluation> checker,
int maxEvaluations,
int maxIterations)
Create a
LeastSquaresProblem
from the given elements. |
static LeastSquaresProblem |
LeastSquaresFactory.weightDiagonal(LeastSquaresProblem problem,
RealVector weights)
Apply a diagonal weight matrix to the
LeastSquaresProblem . |
static LeastSquaresProblem |
LeastSquaresFactory.weightMatrix(LeastSquaresProblem problem,
RealMatrix weights)
Apply a dense weight matrix to the
LeastSquaresProblem . |
Modifier and Type | Method and Description |
---|---|
static LeastSquaresProblem |
LeastSquaresFactory.countEvaluations(LeastSquaresProblem problem,
Incrementor counter)
Count the evaluations of a particular problem.
|
LeastSquaresOptimizer.Optimum |
GaussNewtonOptimizer.optimize(LeastSquaresProblem lsp)
Solve the non-linear least squares problem.
|
LeastSquaresOptimizer.Optimum |
LevenbergMarquardtOptimizer.optimize(LeastSquaresProblem problem)
Solve the non-linear least squares problem.
|
LeastSquaresOptimizer.Optimum |
SequentialGaussNewtonOptimizer.optimize(LeastSquaresProblem lsp)
Solve the non-linear least squares problem.
|
LeastSquaresOptimizer.Optimum |
LeastSquaresOptimizer.optimize(LeastSquaresProblem leastSquaresProblem)
Solve the non-linear least squares problem.
|
static LeastSquaresProblem |
LeastSquaresFactory.weightDiagonal(LeastSquaresProblem problem,
RealVector weights)
Apply a diagonal weight matrix to the
LeastSquaresProblem . |
static LeastSquaresProblem |
LeastSquaresFactory.weightMatrix(LeastSquaresProblem problem,
RealMatrix weights)
Apply a dense weight matrix to the
LeastSquaresProblem . |
Constructor and Description |
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LeastSquaresAdapter(LeastSquaresProblem problem)
Delegate the
LeastSquaresProblem interface to the given implementation. |
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