Generalized Polynomial Modelling
Detection of limit cycles of period-1
drvSucc : Computes the successive derivatives of a time series
extractEq : Extracts Equations from one system
Numerical description of a list of eighteen three-dimensional chaotic ...
Automatic search of polynomial Equations
Tests the numerical integrability of models and classify their dynamic...
Builds the derivative filter
cano2M : Converts a model in canonical form into a matrix form
combiEq : Combine Equations from different sources
Computes the successive derivatives of a time series
Concat Concatenates separated time series
ConcatMulTS Concatenates separated time series (of single or multiples...
Provides the number of polynomial terms pMaxgiven dMax and nVar
Output of the vignette III_Modelling
Output of the vignette VI_Sensitivity
Output of the vignette VII_Retro-Modelling
A subfonction for the numerical integration of polynomial equations pr...
deriveODEwMultiX : A Subfonction for the numerical integration of poly...
Find all possible sets of equation combinations considering an ensembl...
Global Model Identification
GPoM package: Generalized Polynomial Modelling
Generalized Polynomial Modeling
Gram-Schmidt procedure
Numerical Integration of models in ODE of polynomial form
Numerical Integration polynomial ODEs with Multiple eXternal forcing
Generates time series of deterministic-behavior with stochatic perturb...
For the numerical integration of ordinary differential equations with ...
p2dMax : provides the maximum polynomial degree dMaxgiven the number...
For parameter Identification
Polynomial labels order
Estimate the models performance obtained with GPoMoin term of predic...
Model stationnary testing
Generate the conventional order for polynomial terms in a the polynomi...
Estimates the monomial time series
Time series of the Rossler-1976 system
subSysD : Sub-systems Disentangling
Periodic solution test
Time series of three-dimensional chaotic sytems (for vignette `VII_Ret...
Displays the models Equations
visuOutGP : get a quick information of gPoMo output
Weighted inner product
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). The method is described in the article : Mangiarotti S. and Huc M. (2019) <doi:10.1063/1.5081448>.