Package: maclogp 0.1.1
maclogp: Measures of Uncertainty for Model Selection
Following the common types of measures of uncertainty for parameter estimation, two measures of uncertainty were proposed for model selection, see Liu, Li and Jiang (2020) <doi:10.1007/s11749-020-00737-9>. The first measure is a kind of model confidence set that relates to the variation of model selection, called Mac. The second measure focuses on error of model selection, called LogP. They are all computed via bootstrapping. This package provides functions to compute these two measures. Furthermore, a similar model confidence set adapted from Bayesian Model Averaging can also be computed using this package.
Authors:
maclogp_0.1.1.tar.gz
maclogp_0.1.1.zip(r-4.5)maclogp_0.1.1.zip(r-4.4)maclogp_0.1.1.zip(r-4.3)
maclogp_0.1.1.tgz(r-4.4-any)maclogp_0.1.1.tgz(r-4.3-any)
maclogp_0.1.1.tar.gz(r-4.5-noble)maclogp_0.1.1.tar.gz(r-4.4-noble)
maclogp_0.1.1.tgz(r-4.4-emscripten)maclogp_0.1.1.tgz(r-4.3-emscripten)
maclogp.pdf |maclogp.html✨
maclogp/json (API)
# Install 'maclogp' in R: |
install.packages('maclogp', repos = c('https://yuanyuanli96.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/yuanyuanli96/maclogp/issues
- diabetes - Diabetes data
Last updated 2 years agofrom:6e8e329a53. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 16 2024 |
R-4.5-win | OK | Oct 16 2024 |
R-4.5-linux | OK | Oct 16 2024 |
R-4.4-win | OK | Oct 16 2024 |
R-4.4-mac | OK | Oct 16 2024 |
R-4.3-win | OK | Oct 16 2024 |
R-4.3-mac | OK | Oct 16 2024 |
Exports:bmsMACModels_genplot_MAC
Dependencies:BMAdata.tableDEoptimRinlinejsonlitelatticeleapsMatrixmvtnormpcaPPplot.matrixrlistrobustbaserrcovsurvivalXMLyaml
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Bayesian Model Confidence Set | bms |
Diabetes data | diabetes |
Mac and LogP measure | MAC |
Generate all subset models | Models_gen |
Visualize model confidence sets | plot_MAC |