Package: FBMS 1.3
FBMS: Flexible Bayesian Model Selection and Model Averaging
Implements the Mode Jumping Markov Chain Monte Carlo algorithm described in <doi:10.1016/j.csda.2018.05.020> and its Genetically Modified counterpart described in <doi:10.1613/jair.1.13047> as well as the sub-sampling versions described in <doi:10.1016/j.ijar.2022.08.018> for flexible Bayesian model selection and model averaging.
Authors:
FBMS_1.3.tar.gz
FBMS_1.3.zip(r-4.7)FBMS_1.3.zip(r-4.6)FBMS_1.3.zip(r-4.5)
FBMS_1.3.tgz(r-4.6-x86_64)FBMS_1.3.tgz(r-4.6-arm64)FBMS_1.3.tgz(r-4.5-x86_64)FBMS_1.3.tgz(r-4.5-arm64)
FBMS_1.3.tar.gz(r-4.7-arm64)FBMS_1.3.tar.gz(r-4.7-x86_64)FBMS_1.3.tar.gz(r-4.6-arm64)FBMS_1.3.tar.gz(r-4.6-x86_64)
FBMS_1.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
FBMS/json (API)
| # Install 'FBMS' in R: |
| install.packages('FBMS', repos = c('https://jonlachmann.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/jonlachmann/fbms/issues
- abalone - Physical Measurements of 4177 Abalones, a Species of Sea Snail.
- breastcancer - Breast Cancer Wisconsin (Diagnostic) Data Set
- exoplanet - Excerpt from the Open Exoplanet Catalogue Data Set
- SangerData2 - Gene Expression Data for Lymphoblastoid Cell Lines of 210 Unrelated HapMap individuals from four populations
Last updated from:f8c4adad2f. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 242 | ||
| linux-devel-x86_64 | OK | 259 | ||
| source / vignettes | OK | 460 | ||
| linux-release-arm64 | OK | 234 | ||
| linux-release-x86_64 | OK | 254 | ||
| macos-release-arm64 | OK | 182 | ||
| macos-release-x86_64 | OK | 384 | ||
| macos-oldrel-arm64 | OK | 288 | ||
| macos-oldrel-x86_64 | OK | 575 | ||
| windows-devel | OK | 252 | ||
| windows-release | OK | 229 | ||
| windows-oldrel | OK | 191 | ||
| wasm-release | OK | 152 |
Exports:aggrarcsinhcompute_effectscos_degdiagn_ploterfexp_dblfbmsfbms.mlik.mastergaussian.loglikgelugen.params.gmjmcmcgen.params.mjmcmcgen.probs.gmjmcmcgen.probs.mjmcmcget.best.modelget.mpm.modelgmjmcmcgmjmcmc.parallelhsimpute_ximpute_x_predlog_priorlogistic.loglikmarginal.probsmerge_resultsmjmcmcmjmcmc.parallelmodel.stringngelunhsnotnrelup0p05p0p0p0p05p0p1p0p2p0p3p0pm05p0pm1p0pm2p2p3pm05pm1pm2predmeanpredquantilesreluset.transformssigmoidsin_degsqrootstring.populationstring.population.modelstroot
Dependencies:askpassBASbase64encBHbigmemorybigmemory.sribslibcachemclicpp11crosstalkcurldata.tabledigestdplyrevaluatefarverfastglmfastmapfontawesomeFormulafsgenericsGenSAggplot2gluegtablehighrhtmltoolshtmlwidgetshttrisobandjquerylibjsonliteknitrlabelinglaterlatticelazyevallifecyclemagrittrMASSMatrixmemoisemimeopensslotelpillarpkgconfigplotlypromisespurrrr2rR6rappdirsRColorBrewerRcppRcppEigenrlangrmarkdownS7sassscalesstringistringrsystibbletidyrtidyselecttinytextoleranceutf8uuidvctrsviridisLitewithrxfunyaml
