Package: EcoDiet 2.0.1

EcoDiet: Estimating a Diet Matrix from Biotracer and Stomach Content Data

Biotracers and stomach content analyses are combined in a Bayesian hierarchical model to estimate a probabilistic topology matrix (all trophic link probabilities) and a diet matrix (all diet proportions). The package relies on the JAGS software and the 'jagsUI' package to run a Markov chain Monte Carlo approximation of the different variables.

Authors:Pierre-Yves Hernvann [cre, aut], Didier Gascuel [aut], Dorothee Kopp [aut], Marianne Robert [aut], Jerome Guitton [aut], Etienne Rivot [aut], Heloise Thero [aut]

EcoDiet_2.0.1.tar.gz
EcoDiet_2.0.1.zip(r-4.7)EcoDiet_2.0.1.zip(r-4.6)EcoDiet_2.0.1.zip(r-4.5)
EcoDiet_2.0.1.tgz(r-4.6-any)EcoDiet_2.0.1.tgz(r-4.5-any)
EcoDiet_2.0.1.tar.gz(r-4.7-any)EcoDiet_2.0.1.tar.gz(r-4.6-any)
EcoDiet_2.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
EcoDiet/json (API)

# Install 'EcoDiet' in R:
install.packages('EcoDiet', repos = c('https://pyhernvann.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/pyhernvann/ecodiet/issues

Uses libs:
  • jags– Just Another Gibbs Sampler for Bayesian MCMC
  • c++– GNU Standard C++ Library v3
Datasets:

On CRAN:

Conda:

jagscpp

5.35 score 5 stars 15 scripts 265 downloads 7 exports 43 dependencies

Last updated from:53249fd293. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK146
source / vignettesOK257
linux-release-x86_64OK161
macos-release-arm64OK214
macos-oldrel-arm64OK196
windows-develOK100
windows-releaseOK103
windows-oldrelOK97
wasm-releaseOK113

Exports:diagnose_modelplot_dataplot_priorplot_resultspreprocess_datarun_modelwrite_model

Dependencies:clicodacpp11crayondplyrfarverforcatsgenericsGGallyggmcmcggplot2ggstatsgluegtablehmsisobandjagsUIlabelinglatticelifecyclemagrittrMASSpatchworkpillarpkgconfigprettyunitsprogresspurrrR6RColorBrewerrjagsrlangS7scalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr

EcoDiet explored on a realistic example
The configuration without literature data | The configuration with literature data
Rendered fromrealistic_example.Rmdusingknitr::rmarkdown

Last update: 2023-11-14
Started: 2020-01-22

Introduction - How to use EcoDiet
1. Load and check your data | Stomach content data | Biotracer data | 2. Preprocess your data without literature data (Default option) | Preprocess the data | Check the trophic links | 3. Preprocess your data with literature data (Literature option) | Define the priors | Check the trophic links to investigate | 4. Plot the data and the priors | 5. Run the model | Diagnoses | 6. Plot and save the results | The mean results | The probability distributions | 7. Save another variable than $\Pi$ and $\eta$
Rendered fromintroduction_EcoDiet.Rmdusingknitr::rmarkdown

Last update: 2023-11-14
Started: 2020-02-06

How to deal with convergence problems
Issues you can face | Adaptation issues | Convergence issues | How to tackle convergence issues | Increase the number of iterations | Increase the number of adaptation steps | Specify initial values for the model | Conclusions
Rendered fromconvergence_problems.Rmdusingknitr::rmarkdown

Last update: 2022-12-29
Started: 2019-12-05