coda (0.16-1)
Output analysis and diagnostics for MCMC.
http://cran.r-project.org/web/packages/coda
Output analysis and diagnostics for Markov Chain Monte Carlo simulations.
Maintainer:
Martyn Plummer
Author(s): Martyn Plummer [aut, cre, trl], Nicky Best [aut], Kate Cowles [aut], Karen Vines [aut], Deepayan Sarkar [aut], Russell Almond [ctb]
License: GPL (>= 2)
Uses: lattice
Reverse depends: adaptMCMC, adaptsmoFMRI, AdMit, agRee, B2Z, BaM, BAMD, bamdit, BayesComm, bayescount, BayesFactor, bayesGARCH, bayesmix, BayesPanel, bayespref, bayesSurv, bayesTFR, Bayesthresh, BAYSTAR, Bchron, Bergm, bfa, bisoreg, bmk, BRugs, BTSPAS, CARBayes, conting, cplm, dclone, dcmle, ddepn, eiPack, elrm, ergm, femmeR, FME, geiger, gemtc, glmdm, glmmAK, GLMMarp, hierarchicalDS, hSDM, HSROC, HybridMC, hzar, iFad, IsotopeR, JMbayes, kobe, languageR, latentnet, list, marked, MasterBayes, mcgibbsit, MCMCglmm, MCMCpack, mcmcplots, mcsm, MISA, mixAK, mixstock, MplusAutomation, MSBVAR, networkTomography, PhaseType, phcfM, phenology, polySegratioMM, popReconstruct, pscl, qtlbim, R2jags, R2MLwiN, R2WinBUGS, r4ss, ramps, Ratings, rjags, RLadyBug, RMark, runjags, SAVE, scapeMCMC, season, siar, sisus, SPACECAP, spBayes, spdep, spTimer, StateTrace, stocc, stochasticGEM, stochvol, superdiag, survBayes, TBSSurvival, tergm, TESS, WMCapacity, zic
Reverse suggests: AdMit, amen, BayHaz, bcp, CARramps, ddepn, emdbook, ergm, geoRglm, ggmcmc, gmodels, latentnet, latentnetHRT, lme4, MethComp, mlmRev, R2admb, R2BayesX, rbugs, relevent, splinesurv, surveillance, Zelig, zoo
Released 7 months ago.
11 previous versions
- coda_0.15-2. Released 10 months ago.
- coda_0.15-1. Released 10 months ago.
- coda_0.14-7. Released about 1 year ago.
- coda_0.14-6. Released over 1 year ago.
- coda_0.14-5. Released over 1 year ago.
- coda_0.14-4. Released about 2 years ago.
- coda_0.14-2. Released over 2 years ago.
- coda_0.13-5. Released about 3 years ago.
- coda_0.13-4. Released over 4 years ago.
- coda_0.13-2. Released about 5 years ago.
- coda_0.13-1. Released over 5 years ago.
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Reviews
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the essential package for MCMC analysis
doesn’t do Bayesian MCMC (there are many packages to do this), but this is the quintessential package for analyzing the outcome – graphical explor…
bbolker gave coda (0.13-4) a 5. Read the full review.
Related packages: R2WinBUGS, bayesmix, boa, deal, lme4, MasterBayes, MCMCpack, rbugs, bnlearn, MCMCglmm, catnet, BMS, arm, BACCO, BaM, bark, BAS, bayesGARCH, bayesm, BayHaz … (20 best matches, based on common tags.)
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Visit coda on R Graphical Manual.
