Class GaussNewtonOptimizer
- java.lang.Object
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- org.hipparchus.optim.nonlinear.vector.leastsquares.GaussNewtonOptimizer
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- All Implemented Interfaces:
LeastSquaresOptimizer
public class GaussNewtonOptimizer extends Object implements LeastSquaresOptimizer
Gauss-Newton least-squares solver.This class solve a least-square problem by solving the normal equations of the linearized problem at each iteration. Either LU decomposition or Cholesky decomposition can be used to solve the normal equations, or QR decomposition or SVD decomposition can be used to solve the linear system. Cholesky/LU decomposition is faster but QR decomposition is more robust for difficult problems, and SVD can compute a solution for rank-deficient problems.
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Nested Class Summary
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Nested classes/interfaces inherited from interface org.hipparchus.optim.nonlinear.vector.leastsquares.LeastSquaresOptimizer
LeastSquaresOptimizer.Optimum
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Constructor Summary
Constructors Constructor Description GaussNewtonOptimizer()
Creates a Gauss Newton optimizer.GaussNewtonOptimizer(MatrixDecomposer decomposer, boolean formNormalEquations)
Create a Gauss Newton optimizer that uses the given matrix decomposition algorithm to solve the normal equations.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description MatrixDecomposer
getDecomposer()
Get the matrix decomposition algorithm.boolean
isFormNormalEquations()
Get if the normal equations are explicitly formed.LeastSquaresOptimizer.Optimum
optimize(LeastSquaresProblem lsp)
Solve the non-linear least squares problem.String
toString()
GaussNewtonOptimizer
withDecomposer(MatrixDecomposer newDecomposer)
Configure the matrix decomposition algorithm.GaussNewtonOptimizer
withFormNormalEquations(boolean newFormNormalEquations)
Configure if the normal equations should be explicitly formed.
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Constructor Detail
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GaussNewtonOptimizer
public GaussNewtonOptimizer()
Creates a Gauss Newton optimizer.The default for the algorithm is to use QR decomposition and not form normal equations.
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GaussNewtonOptimizer
public GaussNewtonOptimizer(MatrixDecomposer decomposer, boolean formNormalEquations)
Create a Gauss Newton optimizer that uses the given matrix decomposition algorithm to solve the normal equations.- Parameters:
decomposer
- the decomposition algorithm to use.formNormalEquations
- whether the normal equations should be explicitly formed. Iftrue
thendecomposer
is used to solve JTJx=JTr, otherwisedecomposer
is used to solve Jx=r. Ifdecomposer
can only solve square systems then this parameter should betrue
.
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Method Detail
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getDecomposer
public MatrixDecomposer getDecomposer()
Get the matrix decomposition algorithm.- Returns:
- the decomposition algorithm.
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withDecomposer
public GaussNewtonOptimizer withDecomposer(MatrixDecomposer newDecomposer)
Configure the matrix decomposition algorithm.- Parameters:
newDecomposer
- the decomposition algorithm to use.- Returns:
- a new instance.
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isFormNormalEquations
public boolean isFormNormalEquations()
Get if the normal equations are explicitly formed.- Returns:
- if the normal equations should be explicitly formed. If
true
thendecomposer
is used to solve JTJx=JTr, otherwisedecomposer
is used to solve Jx=r.
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withFormNormalEquations
public GaussNewtonOptimizer withFormNormalEquations(boolean newFormNormalEquations)
Configure if the normal equations should be explicitly formed.- Parameters:
newFormNormalEquations
- whether the normal equations should be explicitly formed. Iftrue
thendecomposer
is used to solve JTJx=JTr, otherwisedecomposer
is used to solve Jx=r. Ifdecomposer
can only solve square systems then this parameter should betrue
.- Returns:
- a new instance.
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optimize
public LeastSquaresOptimizer.Optimum optimize(LeastSquaresProblem lsp)
Solve the non-linear least squares problem.- Specified by:
optimize
in interfaceLeastSquaresOptimizer
- Parameters:
lsp
- the problem definition, including model function and convergence criteria.- Returns:
- The optimum.
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