Adding SimpleDFSane to docs

SciML · Feb 7, 2023 · 56b7927 · 56b7927
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diff --git a/docs/src/api/simplenonlinearsolve.md b/docs/src/api/simplenonlinearsolve.md
@@ -10,7 +10,8 @@ Falsi
 SimpleNewtonRaphson
 Broyden
 Klement
-TrustRegion
+SimpleTrustRegion
 Ridder
 Brent
+SimpleDFSane
 ```
diff --git a/docs/src/solvers/NonlinearSystemSolvers.md b/docs/src/solvers/NonlinearSystemSolvers.md
@@ -23,7 +23,7 @@ then `NLSolveJL`'s `:anderson` can be a good choice.
 ## Full List of Methods
 
 !!! note
-    
+
     For the full details on the capabilities and constructors of the different solvers,
     see the Detailed Solver APIs section!
 
@@ -46,15 +46,17 @@ can be used directly to reduce dependencies and improve load times. SimpleNonlin
 methods excel at small problems and problems defined with static arrays.
 
   - `SimpleNewtonRaphson()`: A simplified implementation of the Newton-Raphson method.
-  - `Broyden()`: the classic Broyden's quasi-Newton method.
+  - `Broyden()`: The classic Broyden's quasi-Newton method.
   - `Klement()`: A quasi-Newton method due to Klement. It's supposed to be more efficient
     than Broyden's method, and it seems to be in the cases that have been tried, but more
     benchmarking is required.
   - `SimpleTrustRegion()`: A dogleg trust-region Newton method. Improved globalizing stability
     for more robust fitting over basic Newton methods, though potentially with a cost.
+  - `SimpleDFSane()`: A low-overhead implementation of the df-sane method for solving
+    large-scale nonlinear systems of equations.
 
 !!! note
-    
+
     When used with certain types for the states `u` such as a `Number` or `StaticArray`,
     these solvers are very efficient and non-allocating. These implementations are thus
     well-suited for small systems of equations.