Package: betaBayes 1.0.1
Haiming Zhou
betaBayes: Bayesian Beta Regression
Provides a class of Bayesian beta regression models for the analysis of continuous data with support restricted to an unknown finite support. The response variable is modeled using a four-parameter beta distribution with the mean or mode parameter depending linearly on covariates through a link function. When the response support is known to be (0,1), the above class of models reduce to traditional (0,1) supported beta regression models. Model choice is carried out via the logarithm of the pseudo marginal likelihood (LPML), the deviance information criterion (DIC), and the Watanabe-Akaike information criterion (WAIC). See Zhou and Huang (2022) <doi:10.1016/j.csda.2021.107345>.
Authors:
betaBayes_1.0.1.tar.gz
betaBayes_1.0.1.tar.gz(r-4.5-noble)betaBayes_1.0.1.tar.gz(r-4.4-noble)
betaBayes_1.0.1.tgz(r-4.4-emscripten)betaBayes_1.0.1.tgz(r-4.3-emscripten)
betaBayes.pdf |betaBayes.html✨
betaBayes/json (API)
| # Install 'betaBayes' in R: |
| install.packages('betaBayes', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- covid - COVID-19 County Level Data
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:628c97ed25. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 15 2024 |
| R-4.5-linux-x86_64 | OK | Dec 15 2024 |
Exports:beta4regcox.snell.beta4regpredict.beta4regprint.beta4regprint.summary.beta4regsummary.beta4reg
Dependencies:betaregflexmixFormulalatticelmtestmodeltoolsnnetRcppRcppArmadillosandwichzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Bayesian Beta Regression Models | beta4reg print.beta4reg print.summary.beta4reg summary.beta4reg |
| COVID-19 County Level Data | covid |
| Cox-Snell Diagnostic Plot | cox.snell.beta4reg |
| Predict method for beta4 model fits | predict.beta4reg |
