This algorithm provides a numerical solution to the problem of minimizing (or maximizing) a function. This is more efficient than the Gauss-Newton-like algorithm when starting from points very far from the final minimum (or maximum). A new convergence test is implemented (RDM) in addition to the usual stopping criterion : stopping rule is when the gradients are small enough in the parameters metric (GH-1G).
|Author||Melanie Prague, Viviane Philipps, Cecile Proust-Lima, Boris Hejblum, Daniel Commenges, Amadou Diakite|
|Maintainer||Viviane Philipps <[email protected]>|
|License||GPL (>= 2.0)|
|Package repository||View on CRAN|
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