Package: BayesComm 0.1-2
BayesComm: Bayesian Community Ecology Analysis
Bayesian multivariate binary (probit) regression models for analysis of ecological communities.
Authors:
BayesComm_0.1-2.tar.gz
BayesComm_0.1-2.zip(r-4.5)BayesComm_0.1-2.zip(r-4.4)BayesComm_0.1-2.zip(r-4.3)
BayesComm_0.1-2.tgz(r-4.4-x86_64)BayesComm_0.1-2.tgz(r-4.4-arm64)BayesComm_0.1-2.tgz(r-4.3-x86_64)BayesComm_0.1-2.tgz(r-4.3-arm64)
BayesComm_0.1-2.tar.gz(r-4.5-noble)BayesComm_0.1-2.tar.gz(r-4.4-noble)
BayesComm_0.1-2.tgz(r-4.4-emscripten)BayesComm_0.1-2.tgz(r-4.3-emscripten)
BayesComm.pdf |BayesComm.html✨
BayesComm/json (API)
| # Install 'BayesComm' in R: |
| install.packages('BayesComm', repos = c('https://goldingn.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/goldingn/bayescomm/issues
Last updated 9 years agofrom:6438bc0515. Checks:OK: 1 NOTE: 8. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 04 2024 |
| R-4.5-win-x86_64 | NOTE | Dec 04 2024 |
| R-4.5-linux-x86_64 | NOTE | Dec 04 2024 |
| R-4.4-win-x86_64 | NOTE | Dec 04 2024 |
| R-4.4-mac-x86_64 | NOTE | Dec 04 2024 |
| R-4.4-mac-aarch64 | NOTE | Dec 04 2024 |
| R-4.3-win-x86_64 | NOTE | Dec 04 2024 |
| R-4.3-mac-x86_64 | NOTE | Dec 04 2024 |
| R-4.3-mac-aarch64 | NOTE | Dec 04 2024 |
Dependencies:abindclicodacrayongluehmslatticelifecyclemvtnormpkgconfigprettyunitsprogressR6RcppRcppArmadillorlangvctrs
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Bayesian community ecology analysis | BayesComm-package BayesComm |
| Run a BayesComm model | BC |
| Fit a BayesComm model | BCfit |
| Deviance partitioning | devpart |
| Deviance Information Criterion | DIC |
| Plot bayescomm parameter chains | plot.bayescomm |
| Function to make predictions at new locations | predict.bayescomm |
| Print a bayescomm object | print.bayescomm |
| Extract bayescomm model residuals | residuals.bayescomm |
| Summarise bayescomm parameter chains | summary.bayescomm |
| Window bayescomm objects | window.bayescomm |
