Package: OBsMD 12.0
Marta Nai Ruscone
OBsMD: Objective Bayesian Model Discrimination in Follow-Up Designs
Implements the objective Bayesian methodology proposed in Consonni and Deldossi in order to choose the optimal experiment that better discriminate between competing models, see Deldossi and Nai Ruscone (2020) <doi:10.18637/jss.v094.i02>.
Authors:
OBsMD_12.0.tar.gz
OBsMD_12.0.tar.gz(r-4.5-noble)OBsMD_12.0.tar.gz(r-4.4-noble)
OBsMD_12.0.tgz(r-4.4-emscripten)OBsMD_12.0.tgz(r-4.3-emscripten)
OBsMD.pdf |OBsMD.html✨
OBsMD/json (API)
| # Install 'OBsMD' in R: |
| install.packages('OBsMD', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Datasets:
- BM86.data - Data sets in Box and Meyer
- BM93.e1.data - Example 1 data in Box and Meyer
- BM93.e2.data - Example 2 data in Box and Meyer
- BM93.e3.data - Example 3 data in Box and Meyer
- MetalCutting - Data sets in Edwards, Weese and Palmer
- OBsMD.es5 - OBsMD.es5
- PB12Des - 12-run Plackett-Burman Design Matrix
- Reactor.data - Reactor Experiment Data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 4 months agofrom:6a588c5f0d. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 19 2024 |
| R-4.5-linux-x86_64 | OK | Dec 19 2024 |
Exports:combinationsOBsProbOMD
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Objective Bayesian Model Discrimination in Follow-Up Designs | OBsMD-package OBsMD |
| Data sets in Box and Meyer (1986) | BM86.data |
| Example 1 data in Box and Meyer (1993) | BM93.e1.data |
| Example 2 data in Box and Meyer (1993) | BM93.e2.data |
| Example 3 data in Box and Meyer (1993) | BM93.e3.data |
| Enumerate the Combinations of the Elements of a Vector | combinations |
| Data sets in Edwards, Weese and Palmer (2014) | MetalCutting |
| OBsMD.es5 | OBsMD.es5 |
| Objective Posterior Probabilities from Bayesian Screening Experiments | OBsProb |
| Objective Model Discrimination (OMD) in Follow-Up Experiments | OMD |
| 12-run Plackett-Burman Design Matrix | PB12Des |
| Plotting of Posterior Probabilities from Objective Bayesian Design | plot.OBsProb |
| Printing Objective Posterior Probabilities from Bayesian Design | print.OBsProb |
| Print Optimal OMD Follow-Up Experiments | print.OMD |
| Reactor Experiment Data | Reactor.data |
| Summary of Posterior Probabilities from Objective Bayesian Design | summary.OBsProb |
| Summary of Optimal OMD Follow-Up Experiments | summary.OMD |