Overview | Install and load the package | Required data structure | Configure the responses | Run the candidate-model analysis | Inspect selection and coefficients | Run residual diagnostics | Create figures | Export the analysis | Use the complete generic analysis template | Preflight checks and predictor redundancy | Reproducibility recommendations
Package: ecoGLMM 0.1.4
ecoGLMM: Reproducible Ecological Generalized Linear Mixed Model Pipelines
Fits and compares generalized linear mixed models for multiple ecological responses and environmental predictors. The package supports additive and temporal-interaction candidate models, AICc model selection, likelihood-ratio tests, coefficient extraction, Nakagawa R-squared, simulation-based diagnostics, figures, and spreadsheet exports. Model selection follows Burnham and Anderson (2002, ISBN:9780387953649); marginal and conditional R-squared follow Nakagawa and Schielzeth (2013) <doi:10.1111/j.2041-210x.2012.00261.x>.
Authors:
ecoGLMM_0.1.4.tar.gz
ecoGLMM_0.1.4.zip(r-4.7-any)ecoGLMM_0.1.4.zip(r-4.6-any)ecoGLMM_0.1.4.zip(r-4.5-any)
ecoGLMM_0.1.4.tgz(r-4.6-any)ecoGLMM_0.1.4.tgz(r-4.5-any)
ecoGLMM_0.1.4.tar.gz(r-4.7-any)ecoGLMM_0.1.4.tar.gz(r-4.6-any)
ecoGLMM_0.1.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
ecoGLMM/json (API)
| # Install 'ecoGLMM' in R: |
| install.packages('ecoGLMM', repos = c('https://andre-fcsantos.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/andre-fcsantos/ecoglmm/issues
Last updated from:5c3330c2f1. Checks:9 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel | OK | 140 | ||
| source / vignettes | OK | 224 | ||
| linux-release | OK | 142 | ||
| macos-release | OK | 86 | ||
| macos-oldrel | OK | 116 | ||
| windows-devel | OK | 79 | ||
| windows-release | OK | 89 | ||
| windows-oldrel | OK | 90 | ||
| wasm-release | OK | 123 |
Exports:adjust_betacompare_modelsdiagnose_modelsexport_ecoglmmextract_resultsplot_coefficientsplot_effectplot_selectionprepare_acoustic_indicesprepare_ecodatarun_ecoglmmtest_interactions
Dependencies:apeaskpassbackportsbase64encbayestestRbootbroombslibcachemclicodetoolscolorspacecommonmarkcowplotcpp11crosstalkcurldata.tabledatawizardDerivDHARMadigestdoBydoParalleldplyrevaluatefarverfastmapfontawesomeforeachforecastfracdifffsgapgap.datasetsgenericsggeffectsggplot2glmmTMBgluegtablehighrhtmltoolshtmlwidgetshttpuvhttrinsightisobanditeratorsjquerylibjsonliteknitrlabelinglaterlatticelazyevallifecyclelme4lmtestmagrittrMASSMatrixmemoisemgcvmimeminqamodelrMuMInnlmenloptrnnetnumDerivopensslotelpbkrtestperformancepillarpkgconfigplotlyplyrpromisespurrrqgamR6rappdirsrbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangrmarkdownRTMBS7sandwichsassscalesshinysourcetoolsstringistringrsystibbletidyrtidyselecttimeDatetinytexTMBurcautf8vctrsviridisLitewithrwritexlxfunxtableyamlzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Reproducible ecological GLMM pipelines | ecoGLMM-package ecoGLMM |
| Keep proportions inside the open interval (0, 1) | adjust_beta |
| Compare a candidate set using corrected Akaike information criterion | compare_models |
| Run DHARMa diagnostics for selected models | diagnose_models |
| Export ecoGLMM results to an output directory | export_ecoglmm |
| Extract coefficients and model-level statistics | extract_results |
| Plot coefficients and confidence intervals | plot_coefficients |
| Plot the marginal effect of a selected model | plot_effect |
| Plot model-selection results | plot_selection |
| Prepare common acoustic-index transformations | prepare_acoustic_indices |
| Validate and prepare ecological modelling data | prepare_ecodata |
| Run an ecological GLMM candidate-model pipeline | run_ecoglmm |
| Likelihood-ratio tests for additive versus interaction models | test_interactions |