Package: GPoM 1.4
Mireille Huc
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). The method is described in the article : Mangiarotti S. and Huc M. (2019) <doi:10.1063/1.5081448>.
Authors:
GPoM_1.4.tar.gz
GPoM_1.4.tar.gz(r-4.5-noble)GPoM_1.4.tar.gz(r-4.4-noble)
GPoM_1.4.tgz(r-4.4-emscripten)GPoM_1.4.tgz(r-4.3-emscripten)
GPoM.pdf |GPoM.html✨
GPoM/json (API)
# Install 'GPoM' in R: |
install.packages('GPoM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- NDVI - A time series of vegetation index measured from satellite
- P1FxCh - A data set for testing periodicity
- P1FxChP2 - A data set for testing periodicity
- RosYco - Twelve Rossler-1976 time series
- Ross76 - Time series of the Rossler-1976 system
- TS - Time series resulting from the integration of a non stationary system
- TSallMod_nVar3_dMax2 - Time series of three-dimensional chaotic sytems
- allMod_nVar3_dMax2 - Numerical description of a list of eighteen three-dimensional chaotic sytems
- allToTest - A list providing the description of six models tested by the function 'autoGPoMoTest'.
- data_vignetteIII - Output of the vignette 'III_Modelling'
- data_vignetteVI - Output of the vignette 'VI_Sensitivity'
- data_vignetteVII - Output of the vignette 'VII_Retro-Modelling'
- svrlTS - A data set for the global modeling of time series in association
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:30d30bc8ef. Checks:OK: 1 WARNING: 1. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 13 2024 |
R-4.5-linux | WARNING | Dec 13 2024 |
Exports:autoGPoMoSearchautoGPoMoTestbDrvFiltcano2McombiEqcompDerivconcatconcatMulTSd2pMaxderivODEwMultiXdrvSuccfindAllSetsgloMoIdgPoMonumicanonumiMultiXnuminoisyp2dMaxpoLabspredictabpTimEvregOrdregSeriessubSysDtestPvisuEqvisuOutGPwInProd
Dependencies:base64encbslibcachemclideSolvedigestevaluatefastmapfloatfontawesomefsgluehighrhtmltoolshtmlwidgetsjquerylibjsonliteknitrlifecyclemagrittrmemoisemimeR6rappdirsrglrlangrmarkdownsasstinytexxfunyaml
GPoM : 1 Conventions
Rendered fromb1_Conventions.Rmd
usingknitr::rmarkdown
on Dec 13 2024.Last update: 2020-02-18
Started: 2018-07-26
GPoM : 2 PreProcessing
Rendered fromb2_PreProcessing.Rmd
usingknitr::rmarkdown
on Dec 13 2024.Last update: 2020-02-18
Started: 2018-07-26
GPoM : 3 Modelling
Rendered fromb3_Modelling.Rmd
usingknitr::rmarkdown
on Dec 13 2024.Last update: 2023-06-16
Started: 2018-07-26
GPoM : 4 Visualization of the outputs
Rendered fromb4_VisualizeOutputs.Rmd
usingknitr::rmarkdown
on Dec 13 2024.Last update: 2020-02-18
Started: 2018-07-26
GPoM : 5 Models predictability
Rendered fromb5_Predictability.Rmd
usingknitr::rmarkdown
on Dec 13 2024.Last update: 2020-02-18
Started: 2018-07-26
GPoM : 6 Approach sensitivity
Rendered fromb6_Sensitivity.Rmd
usingknitr::rmarkdown
on Dec 13 2024.Last update: 2020-02-18
Started: 2018-07-26
GPoM : 7 Retro-modelling
Rendered fromb7_Retro-modelling.Rmd
usingknitr::rmarkdown
on Dec 13 2024.Last update: 2020-02-18
Started: 2018-07-26
GPoM : General introduction
Rendered froma_GeneralIntro.Rmd
usingknitr::rmarkdown
on Dec 13 2024.Last update: 2020-02-18
Started: 2018-07-26