@@ -71,13 +71,19 @@ methods excel at small problems and problems defined with static arrays.
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- ` SimpleNewtonRaphson() ` : A simplified implementation of the Newton-Raphson method.
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- ` Broyden() ` : The classic Broyden's quasi-Newton method.
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+ - ` LBroyden() ` : A low-memory Broyden implementation, similar to L-BFGS. This method is
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+ common in machine learning contexts but is known to be unstable in comparison to many
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+ other choices.
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- ` Klement() ` : A quasi-Newton method due to Klement. It's supposed to be more efficient
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than Broyden's method, and it seems to be in the cases that have been tried, but more
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benchmarking is required.
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- ` SimpleTrustRegion() ` : A dogleg trust-region Newton method. Improved globalizing stability
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for more robust fitting over basic Newton methods, though potentially with a cost.
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- ` SimpleDFSane() ` : A low-overhead implementation of the df-sane method for solving
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large-scale nonlinear systems of equations.
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+ - ` SimpleHalley() ` : A low-overhead implementation of the Halley method. This is a higher order
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+ method and thus can converge faster to low tolerances than a Newton method. Requires higher
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+ order derivatives, so best used when automatic differentiation is available.
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!!! note
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@@ -102,7 +108,6 @@ This is a wrapper package for importing solvers from NLsolve.jl into the SciML i
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Submethod choices for this algorithm include:
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- - ` :fixedpoint ` : Fixed-point iteration
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- ` :anderson ` : Anderson-accelerated fixed-point iteration
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- ` :newton ` : Classical Newton method with an optional line search
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- ` :trust_region ` : Trust region Newton method (the default choice)
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