Package: EcoDiet 2.0.1
Pierre-Yves Hernvann
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:
EcoDiet_2.0.1.tar.gz
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✨
card.svg |card.png
EcoDiet/json (API)
NEWS
| # Install 'EcoDiet' in R: |
| install.packages('EcoDiet', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/pyhernvann/ecodiet/issues
- jags– Just Another Gibbs Sampler for Bayesian MCMC - binary JAGS is Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. JAGS was written with three aims in mind: * To have an engine for the BUGS language that runs on Unix * To be extensible, allowing users to write their own functions, distributions and samplers. * To be a plaftorm for experimentation with ideas in Bayesian modelling This package contains the 'jags' binary as well as the associated shared library modules loaded by the binary.
- c++– GNU Standard C++ Library v3
- mcmc_output_example - The MCMC output for running the example dataset
Last updated from:ccbbaba659. Checks:4 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 158 | ||
| source / vignettes | OK | 250 | ||
| linux-release-x86_64 | OK | 165 | ||
| wasm-release | OK | 143 |
Exports:diagnose_modelplot_dataplot_priorplot_resultspreprocess_datarun_modelwrite_model
Dependencies:clicodacpp11crayondplyrfarverforcatsgenericsGGallyggmcmcggplot2ggstatsgluegtablehmsisobandjagsUIlabelinglatticelifecyclemagrittrMASSpatchworkpillarpkgconfigprettyunitsprogresspurrrR6RColorBrewerrjagsrlangS7scalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithr
Introduction - How to use EcoDiet
Rendered fromintroduction_EcoDiet.Rmdusingknitr::rmarkdownon Jun 06 2026.Last update: 2024-03-26
Started: 2020-03-05
EcoDiet explored on a realistic example
Rendered fromrealistic_example.Rmdusingknitr::rmarkdownon Jun 06 2026.Last update: 2024-03-26
Started: 2020-03-05
How to deal with convergence problems
Rendered fromconvergence_problems.Rmdusingknitr::rmarkdownon Jun 06 2026.Last update: 2023-01-06
Started: 2020-03-05
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Diagnose EcoDiet model | diagnose_model |
| Example biotracer data | example_biotracer_data |
| Example literature diets | example_literature_diets |
| Example stomach data | example_stomach_data |
| The MCMC output for running the example dataset | mcmc_output_example |
| Plot the input data | plot_data |
| Plot the prior means or probability distribution(s) | plot_prior |
| Plot the posterior means or probability distribution(s) | plot_results |
| Check and preprocess the data | preprocess_data |
| Realistic biotracer data | realistic_biotracer_data |
| Realistic literature diets | realistic_literature_diets |
| Realistic stomach data | realistic_stomach_data |
| Run the EcoDiet model | run_model |
| Write the EcoDiet model in BUGS | write_model |
