Package: bayesreg 1.2
Daniel F. Schmidt
bayesreg: Bayesian Regression Models with Global-Local Shrinkage Priors
Fits linear or generalized linear regression models using Bayesian global-local shrinkage prior hierarchies as described in Polson and Scott (2010) <doi:10.1093/acprof:oso/9780199694587.003.0017>. Provides an efficient implementation of ridge, lasso, horseshoe and horseshoe+ regression with logistic, Gaussian, Laplace, Student-t, Poisson or geometric distributed targets using the algorithms summarized in Makalic and Schmidt (2016) <arxiv:1611.06649>.
Authors:
bayesreg_1.2.tar.gz
bayesreg_1.2.tar.gz(r-4.5-noble)bayesreg_1.2.tar.gz(r-4.4-noble)
bayesreg_1.2.tgz(r-4.4-emscripten)bayesreg_1.2.tgz(r-4.3-emscripten)
bayesreg.pdf |bayesreg.html✨
bayesreg/json (API)
| # Install 'bayesreg' in R: |
| install.packages('bayesreg', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- spambase - Spambase
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:46b479172d. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 15 2024 |
| R-4.5-linux | OK | Sep 15 2024 |
Exports:bayesreg
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Getting started with the bayesreg package | bayesreg-package |
| Fitting Bayesian Regression Models with Continuous Shrinkage Priors | bayesreg |
| Prediction method for Bayesian penalised regression ('bayesreg') models | predict.bayesreg |
| Spambase | spambase |
| Summarization method for Bayesian penalised regression ('bayesreg') models | summary.bayesreg |