Package: runjags 2.2.3-8
Matthew Denwood
runjags: Interface Utilities, Model Templates, Parallel Computing Methods and Additional Distributions for MCMC Models in JAGS
User-friendly interface utilities for MCMC models via Just Another Gibbs Sampler (JAGS), facilitating the use of parallel (or distributed) processors for multiple chains, automated control of convergence and sample length diagnostics, and evaluation of the performance of a model using drop-k validation or against simulated data. Template model specifications can be generated using a standard lme4-style formula interface to assist users less familiar with the BUGS syntax. A JAGS extension module provides additional distributions including the Pareto family of distributions, the DuMouchel prior and the half-Cauchy prior.
Authors:
runjags_2.2.3-8.tar.gz
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runjags_2.2.3-8.tgz(r-4.4-x86_64)runjags_2.2.3-8.tgz(r-4.4-arm64)runjags_2.2.3-8.tgz(r-4.3-x86_64)runjags_2.2.3-8.tgz(r-4.3-arm64)
runjags_2.2.3-8.tar.gz(r-4.5-noble)runjags_2.2.3-8.tar.gz(r-4.4-noble)
runjags.pdf |runjags.html✨
runjags/json (API)
| # Install 'runjags' in R: |
| install.packages('runjags', repos = c('https://ku-awdc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/ku-awdc/runjags/issues
Last updated 6 months agofrom:4b13e3f22d. Checks:OK: 1 WARNING: 8. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 13 2024 |
| R-4.5-win-x86_64 | WARNING | Sep 13 2024 |
| R-4.5-linux-x86_64 | WARNING | Sep 13 2024 |
| R-4.4-win-x86_64 | WARNING | Sep 13 2024 |
| R-4.4-mac-x86_64 | WARNING | Sep 13 2024 |
| R-4.4-mac-aarch64 | WARNING | Sep 13 2024 |
| R-4.3-win-x86_64 | WARNING | Sep 13 2024 |
| R-4.3-mac-x86_64 | WARNING | Sep 13 2024 |
| R-4.3-mac-aarch64 | WARNING | Sep 13 2024 |
Exports:add.summaryas.jagsas.runjagsaskautoextend.jagsautoextend.JAGSautorun.jagsautorun.JAGScleanup.jagscleanup.JAGScombine.jagscombine.JAGScombine.mcmccombine.MCMCcontrasts.mcmccontrasts.MCMCdivide.jagsdivide.JAGSdrop.kdrop.k.jagsdrop.k.JAGSdump.formatextend.jagsextend.JAGSextractextract.runjagsfailed.jagsfailed.JAGSfailedjagsfindjagsfindJAGSis.runjagslist.formatload.runjagsmoduleload.runJAGSmodulenew_uniqueprec2sdread.jagsfileread.JAGSfileread.winbugsread.WinBUGSresults.jagsresults.JAGSrun.jagsrun.JAGSrun.jags.studyrun.JAGS.studyrunjags.getOptionrunjags.optionstemplate_huiwaltertemplate.jagstemplate.JAGStestjagstestJAGStimestringunload.runjagsmoduleunload.runJAGSmodulewrite.jagsfilewrite.JAGSfile
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Summary statistics and plot methods for runjags class objects | add.summary plot.runjags plot.runjagsplots print.runjags print.runjagsplots summary.runjags |
| Obtain Input from User With Error Handling | ask |
| Run or extend a user-specified Bayesian MCMC model in JAGS with automatically calculated run-length and convergence diagnostics | autoextend.JAGS autoextend.jags autorun.JAGS autorun.jags |
| Combining and dividing runjags and MCMC objects | combine.JAGS combine.jags combine.MCMC combine.mcmc divide.JAGS divide.jags |
| Conversion Between a Named List and a Character String in the R Dump Format | dump.format dump.list.format list.format |
| Extract peripheral information from runjags objects | dic.runjags extract extract.jags extract.runjags |
| Attempt to Locate a JAGS Install | findJAGS findjags |
| Load the internal JAGS module provided by runjags | load.runJAGSmodule load.runjagsmodule unload.runJAGSmodule unload.runjagsmodule |
| Mutate functions to be used with runjags summary methods | contrasts.MCMC contrasts.mcmc mutate.functions prec2sd |
| Create a Unique Filename | new_unique |
| Extract Any Models, Data, Monitored Variables or Initial Values As Character Vectors from a JAGS or WinBUGS Format Textfile | read.JAGSfile read.jagsfile read.WinBUGS read.winbugs |
| Importing of saved JAGS simulations with partial error recovery | results.JAGS results.jags |
| Run or extend a user-specified Bayesian MCMC model in JAGS from within R | extend.JAGS extend.jags run.JAGS run.jags |
| Drop-k and simulated dataset studies using JAGS | drop.k drop.k.JAGS drop.k.jags run.JAGS.study run.jags.study |
| The runjags class and available S3 methods | as.jags as.jags.default as.jags.runjags as.mcmc.list.runjags as.mcmc.runjags as.runjags as.runjags.default as.runjags.jags cleanup.JAGS cleanup.jags failed.JAGS failed.jags failedjags fitted.runjags is.runjags predict.runjags residuals.runjags runjags-class runjagsclass runjagsstudy-class runjagsstudyclass |
| Options for the runjags package | runJAGS.getOption runjags.getOption runJAGS.options runjags.options |
| Print methods for runjags helper classes | plot.runjagsstudy print.crosscorrstats print.dicstats print.failedjags print.gelman.with.target print.gelmanwithtarget print.mcsestats print.rjagsoutput print.runjagsbginfo print.runjagsdata print.runjagsinits print.runjagsmodel print.runjagsoutput print.runjagsstudy runjags.printmethods summary.runjagsstudy |
| Create a Hui-Walter model based on paired test data for an arbitrary number of tests and populations | template_huiwalter |
| Generate a generalised linear mixed model (GLMM) specification in JAGS | template.JAGS template.jags |
| Analyse the System to Check That JAGS Is Installed | testJAGS testjags |
| Calculate the Elapsed Time in Sensible Units | timestring |
| Write a complete JAGS model to a text file | write.JAGSfile write.jagsfile |
