GPoM: Generalized Polynomial Modelling

Platform dedicated to the Global Modelling technique. Its aim is to obtain ordinary differential equations of polynomial form directly from time series. It can be applied to single or multiple time series under various conditions of noise, time series lengths, sampling, etc. This platform is developped at the Centre d'Etudes Spatiales de la Biosphere (CESBIO), UMR 5126 UPS/CNRS/CNES/IRD, 18 av. Edouard Belin, 31401 TOULOUSE, FRANCE. The developments were funded by the French program Les Enveloppes Fluides et l'Environnement (LEFE, MANU, projets GloMo, SpatioGloMo and MoMu). The French program Defi InFiNiTi (CNRS) and PNTS are also acknowledged (projects Crops'IChaos and Musc & SlowFast).

Version: 1.2
Depends: R (≥ 2.10), deSolve, rgl
Suggests: testthat, knitr, rmarkdown, signal, float
Published: 2018-07-26
Author: Sylvain Mangiarotti [aut], Flavie Le Jean [ctb], Malika Chassan [ctb], Laurent Drapeau [ctb], Mireille Huc [cre]
Maintainer: Mireille Huc <mireille.huc at>
License: CeCILL-2
NeedsCompilation: no
CRAN checks: GPoM results


Reference manual: GPoM.pdf
Vignettes: GPoM : General introduction
GPoM : 1 Conventions
GPoM : 2 PreProcessing
GPoM : 3 Modelling
GPoM : 4 Visualization of the outputs
GPoM : 5 Models predictability
GPoM : 6 Models sensitivity
GPoM : 7 Retro-modelling
Package source: GPoM_1.2.tar.gz
Windows binaries: r-devel:, r-devel-gcc8:, r-release:, r-oldrel:
OS X binaries: r-release: GPoM_1.2.tgz, r-oldrel: GPoM_1.2.tgz
Old sources: GPoM archive

Reverse dependencies:

Reverse depends: GPoM.FDLyapu


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