Package: abms 0.1
Francisco Segovia
abms: Augmented Bayesian Model Selection for Regression Models
Tools to perform model selection alongside estimation under Linear, Logistic, Negative binomial, Quantile, and Skew-Normal regression. Under the spike-and-slab method, a probability for each possible model is estimated with the posterior mean, credibility interval, and standard deviation of coefficients and parameters under the most probable model.
Authors:
abms_0.1.tar.gz
abms_0.1.tar.gz(r-4.5-noble)abms_0.1.tar.gz(r-4.4-noble)
abms_0.1.tgz(r-4.4-emscripten)abms_0.1.tgz(r-4.3-emscripten)
abms.pdf |abms.html✨
abms/json (API)
| # Install 'abms' in R: |
| install.packages('abms', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/sircornflake/bms/issues
- ens - Chilean National Health Survey
Last updated 3 days agofrom:a3da752524. Checks:3 OK. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 13 2025 |
| R-4.5-linux | OK | Mar 13 2025 |
| R-4.4-linux | OK | Mar 13 2025 |
Exports:gen_base_binomial_reggen_base_NegBinomial_reggibbs_abmsrCRTsummary_gibbswomack
Dependencies:BayesLogitGIGrvgmvtnormtruncnorm
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Chilean National Health Survey (2016-2017) | ens |
| Logistic Regression Data generator | gen_base_binomial_reg |
| Negative Binomial Regression Data generator | gen_base_NegBinomial_reg |
| Bayesian variable selection models via a spike-and-slab methodology. | gibbs_abms |
| Title | rCRT |
| Summary function for abms objects | summary_gibbs |
| For internal use Womack prior | womack |