marqLevAlg: A Parallelized Algorithm for Least-Squares Curve Fitting

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).

Getting started

Package details

AuthorMelanie Prague, Viviane Philipps, Cecile Proust-Lima, Boris Hejblum, Daniel Commenges, Amadou Diakite
MaintainerViviane Philipps <[email protected]>
LicenseGPL (>= 2.0)
Package repositoryView on CRAN
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marqLevAlg documentation built on Sept. 20, 2019, 5:04 p.m.