Package: bfw 0.4.2
Øystein Olav Skaar
bfw: Bayesian Framework for Computational Modeling
Derived from the work of Kruschke (2015, <ISBN:9780124058880>), the present package aims to provide a framework for conducting Bayesian analysis using Markov chain Monte Carlo (MCMC) sampling utilizing the Just Another Gibbs Sampler ('JAGS', Plummer, 2003, <https://mcmc-jags.sourceforge.io>). The initial version includes several modules for conducting Bayesian equivalents of chi-squared tests, analysis of variance (ANOVA), multiple (hierarchical) regression, softmax regression, and for fitting data (e.g., structural equation modeling).
Authors:
bfw_0.4.2.tar.gz
bfw_0.4.2.zip(r-4.5)bfw_0.4.2.zip(r-4.4)bfw_0.4.2.zip(r-4.3)
bfw_0.4.2.tgz(r-4.4-any)bfw_0.4.2.tgz(r-4.3-any)
bfw_0.4.2.tar.gz(r-4.5-noble)bfw_0.4.2.tar.gz(r-4.4-noble)
bfw_0.4.2.tgz(r-4.4-emscripten)bfw_0.4.2.tgz(r-4.3-emscripten)
bfw.pdf |bfw.html✨
bfw/json (API)
NEWS
| # Install 'bfw' in R: |
| install.packages('bfw', repos = c('https://oeysan.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/oeysan/bfw/issues
- Cats - Dataset with Cats
bayesian-data-analysisbayesian-statisticsjagsmcmcpsychological-science
Last updated 3 years agofrom:9d2b94c2b4. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 11 2024 |
| R-4.5-win | OK | Oct 11 2024 |
| R-4.5-linux | OK | Oct 11 2024 |
| R-4.4-win | OK | Oct 11 2024 |
| R-4.4-mac | OK | Oct 11 2024 |
| R-4.3-win | OK | Oct 11 2024 |
| R-4.3-mac | OK | Oct 11 2024 |
Exports:AddNamesbfwCapWordsChangeNamesComputeHDIContrastNamesDiagMCMCDistinctColorsETAFileNameFindEnvironmentFlattenListGammaDistGetRangeInterleaveInverseHDILayoutMatrixCombnMergeMCMCMultiGrepNormalizePadVectorParseNumberParsePlotPlotCirclizePlotDataPlotMeanPlotNominalPlotParamReadFileRemoveEmptyRemoveGarbageRemoveSpacesRunContrastsRunMCMCSingleStringStatsBernoulliStatsCovariateStatsFitStatsKappaStatsMeanStatsMetricStatsNominalStatsRegressionStatsSoftmaxSumMCMCSumToZeroTidyCodeTrimTrimSplitVectorSub
Dependencies:askpassbase64enccirclizeclicodacolorspacecpp11data.tabledigestdplyrfansifarverfastmapfontBitstreamVerafontLiberationfontquivergdtoolsgenericsggplot2GlobalOptionsgluegtablehtmltoolsisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmeofficeropensslpillarpkgconfigplyrpngR6raggRColorBrewerRcpprlangrunjagsrvgscalesshapesyssystemfontstextshapingtibbletidyselectutf8uuidvctrsviridisLitewithrxml2zip
Fit Latent Data
Rendered fromfit_latent_data.Rmdusingknitr::rmarkdownon Oct 11 2024.Last update: 2022-02-22
Started: 2022-02-22
Fit Observed Data
Rendered fromfit_observed_data.Rmdusingknitr::rmarkdownon Oct 11 2024.Last update: 2022-02-22
Started: 2022-02-22
Plot Data
Rendered fromplot_mean.Rmdusingknitr::rmarkdownon Oct 11 2024.Last update: 2022-02-22
Started: 2022-02-22
Predict Metric
Rendered frommetric.Rmdusingknitr::rmarkdownon Oct 11 2024.Last update: 2022-02-22
Started: 2022-02-22
Regression
Rendered fromregression.Rmdusingknitr::rmarkdownon Oct 11 2024.Last update: 2022-02-22
Started: 2022-02-22
