Package: TBFmultinomial 0.1.3
TBFmultinomial: TBF Methodology Extension for Multinomial Outcomes
Extends the test-based Bayes factor (TBF) methodology to multinomial regression models and discrete time-to-event models with competing risks. The TBF methodology has been well developed and implemented for the generalised linear model [Held et al. (2015) <doi:10.1214/14-STS510>] and for the Cox model [Held et al. (2016) <doi:10.1002/sim.7089>].
Authors:
TBFmultinomial_0.1.3.tar.gz
TBFmultinomial_0.1.3.zip(r-4.7-any)TBFmultinomial_0.1.3.zip(r-4.6-any)TBFmultinomial_0.1.3.zip(r-4.5-any)
TBFmultinomial_0.1.3.tgz(r-4.6-any)TBFmultinomial_0.1.3.tgz(r-4.5-any)
TBFmultinomial_0.1.3.tar.gz(r-4.7-any)TBFmultinomial_0.1.3.tar.gz(r-4.6-any)
TBFmultinomial_0.1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
TBFmultinomial/json (API)
| # Install 'TBFmultinomial' in R: |
| install.packages('TBFmultinomial', repos = c('https://rachelhey.r-universe.dev', 'https://cloud.r-project.org')) |
Datasets:
- VAP_data - Data on VAP acquistion in one ICU
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:b616719172. Checks:8 OK, 1 ERROR. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | OK | 165 | ||
| source / vignettes | ERROR | 3524 | ||
| linux-release-x86_64 | OK | 131 | ||
| macos-release-arm64 | OK | 187 | ||
| macos-oldrel-arm64 | OK | 256 | ||
| windows-devel | OK | 84 | ||
| windows-release | OK | 85 | ||
| windows-oldrel | OK | 80 | ||
| wasm-release | OK | 108 |
Exports:AIC_BIC_based_marginalLikelihoodCSVSmodel_priorsPIPs_by_landmarkingplot_CSVSPMPpostInclusionProbsample_multinomialTBFTBF_ingredients
Dependencies:cligluelifecyclemagrittrnnetplotrixrlangstringistringrvctrsVGAM
Vignettes and/or manual for this package failed to build, some documents may be unavailable. Please inspect thebuild logs for more information.
TBFmultinomial
Last update: 2018-10-12
Started: 2017-11-02
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Objective Bayesian variable selection for multinomial regression and discrete time-to-event models with competing risks | TBFmultinomial-package TBFmultinomial |
| Marginal likelihoods based on AIC or BIC | AIC_BIC_based_marginalLikelihood |
| Formulas of all the candidate models | all_formulas |
| Convert a PMP object into a data frame | as.data.frame.PMP |
| Cause-specific variable selection (CSVS) | CSVS |
| Prior model probability | model_priors |
| Posterior inclusion probabilities (PIPs) by landmarking | PIPs_by_landmarking |
| Plot a CSVS object | plot_CSVS |
| Posterior model probability | PMP |
| Class for PMP objects | PMP-class |
| Posterior inclusion probability (PIP) | postInclusionProb |
| Samples from a PMP object | sample_multinomial |
| Test-based Bayes factor | TBF |
| Ingredients to calculate the TBF | TBF_ingredients |
| Data on VAP acquistion in one ICU | VAP_data |
