Package: marqLevAlg
Type: Package
Title: A Parallelized Algorithm for Least-Squares Curve Fitting
Version: 2.0.1
Date: 2019-09-19
Author: Melanie Prague, Viviane Philipps, Cecile Proust-Lima, Boris Hejblum, Daniel Commenges, Amadou Diakite
Maintainer: Viviane Philipps <viviane.philipps@u-bordeaux.fr>
Depends: R (>= 2.0.0)
LazyLoad: yes
Description: 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).
License: GPL (>= 2.0)
BugReports: http://github.com/VivianePhilipps/marqLevAlgParallel/issues
NeedsCompilation: yes
Imports: doParallel, foreach
Suggests: microbenchmark
RoxygenNote: 6.0.1
Packaged: 2019-09-19 13:16:49 UTC; vp3
Repository: CRAN
Date/Publication: 2019-09-20 09:30:04 UTC
