Package: bmm 1.0.0
bmm: Easy and Accessible Bayesian Measurement Models Using 'brms'
Fit computational and measurement models using full Bayesian inference. The package provides a simple and accessible interface by translating complex domain-specific models into 'brms' syntax, a powerful and flexible framework for fitting Bayesian regression models using 'Stan'. The package is designed so that users can easily apply state-of-the-art models in various research fields, and so that researchers can use it as a new model development framework.
Authors:
bmm_1.0.0.tar.gz
bmm_1.0.0.zip(r-4.5)bmm_1.0.0.zip(r-4.4)bmm_1.0.0.zip(r-4.3)
bmm_1.0.0.tgz(r-4.4-any)bmm_1.0.0.tgz(r-4.3-any)
bmm_1.0.0.tar.gz(r-4.5-noble)bmm_1.0.0.tar.gz(r-4.4-noble)
bmm_1.0.0.tgz(r-4.4-emscripten)bmm_1.0.0.tgz(r-4.3-emscripten)
bmm.pdf |bmm.html✨
bmm/json (API)
NEWS
# Install 'bmm' in R: |
install.packages('bmm', repos = c('https://popov-lab.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/venpopov/bmm/issues
- oberauer_lin_2017 - Data from Experiment 1 reported by Oberauer & Lin
- zhang_luck_2008 - Data from Experiment 2 reported by Zhang & Luck
Last updated 6 months agofrom:8ada976031 (on v1.0.1). Checks:OK: 5 NOTE: 2. Indexed: no.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 19 2024 |
R-4.5-win | NOTE | Nov 19 2024 |
R-4.5-linux | NOTE | Nov 19 2024 |
R-4.4-win | OK | Nov 19 2024 |
R-4.4-mac | OK | Nov 19 2024 |
R-4.3-win | OK | Nov 19 2024 |
R-4.3-mac | OK | Nov 19 2024 |
Exports:%>%bmfbmf2bfbmmbmm_optionsbmmformulac_bessel2sqrtexpc_sqrtexp2besselcalc_error_relative_to_nontargetscheck_dataconfigure_modelconfigure_priordefault_priordeg2raddimmdmixture2pdmixture3pdsdmfit_infofit_modelimmIMMabcIMMbscIMMfullk2sdmixture2pmixture3ppimmpmixture2ppmixture3ppostprocess_brmprint_pretty_models_mdpsdmqimmqmixture2pqmixture3pqsdmrad2degrestructurerevert_postprocess_brmrimmrmixture2prmixture3prsdmsdmsdmSimplesoftmaxsoftmaxinvstancodestandatasupported_modelsuse_model_templatewrap
Dependencies:abindbackportsbayesplotBHbridgesamplingbrmsBrobdingnagcallrcheckmateclicodacodetoolscolorspacecpp11crayondescdigestdistributionaldplyrfansifarverfsfuturefuture.applygenericsggplot2ggridgesglobalsgluegridExtragtableinlineisobandlabelinglatticelifecyclelistenvloomagrittrMASSMatrixmatrixStatsmgcvmunsellmvtnormnleqslvnlmenumDerivparallellypillarpkgbuildpkgconfigplyrposteriorprocessxpspurrrQuickJSRR6RColorBrewerRcppRcppEigenRcppParallelreshape2rlangrstanrstantoolsscalesStanHeadersstringistringrtensorAtibbletidyrtidyselectutf8vctrsviridisLitewithr