
WinBUGS
 Referenced in 554 articles
[sw04492]
 BUGS project, which aims to make practical MCMC methods available to applied statisticians. WinBUGS...

GMRFLib
 Referenced in 222 articles
[sw06641]
 only possible using Markov Chain Monte Carlo (MCMC) techniques. The preeminent experts in the field ... aspects, construct fast and reliable algorithms for MCMC inference, and provide an online Clibrary...

BUGS
 Referenced in 294 articles
[sw07885]
 statistical models using Markov chain Monte Carlo (MCMC) methods. The project began...

CODA
 Referenced in 188 articles
[sw04290]
 package coda: Output analysis and diagnostics for MCMC , Output analysis and diagnostics for Markov Chain ... output from Markov Chain Monte Carlo (MCMC) simulations, as well as diagnostic tests of convergence...

spBayes
 Referenced in 251 articles
[sw10160]
 involves computationally intensive Markov chain Monte Carlo (MCMC) methods whose efficiency depends upon the specific...

JAGS
 Referenced in 124 articles
[sw08040]
 hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. JAGS...

Stan
 Referenced in 92 articles
[sw10200]
 language implementing full Bayesian statistical inference with MCMC sampling (NUTS, HMC) and penalized maximum likelihood...

MLwiN
 Referenced in 82 articles
[sw04837]
 likelihood estimation and Markov Chain Monte Carlo (MCMC) methods. MLwiN is based on an earlier...

OpenBUGS
 Referenced in 62 articles
[sw08316]
 expert system’, which determines an appropriate MCMC (Markov chain Monte Carlo) scheme (based...

Mcmcpack
 Referenced in 37 articles
[sw07974]
 MCMCpack: Markov chain Monte Carlo (MCMC) Package. This package contains functions to perform Bayesian inference ... Library Version 1.0.3. All models return coda mcmc objects that can then be summarized using...

BayesTree
 Referenced in 50 articles
[sw07995]
 accomplished via an iterative Bayesian backfitting MCMC algorithm that generates samples from a posterior. Effectively...

rjags
 Referenced in 30 articles
[sw08039]
 package rjags: Bayesian graphical models using MCMC. Interface to the JAGS MCMC library. The rjags ... analysis. JAGS uses Markov Chain Monte Carlo (MCMC) to generate a sequence of dependent samples...

SSS
 Referenced in 24 articles
[sw07794]
 approaches such as Markov chain Monte Carlo (MCMC) methods are often infeasible or ineffective ... from gene expression cancer genomics, comparisons with MCMC and other methods, and theoretical and simulation...

MrBayes
 Referenced in 31 articles
[sw07715]
 models. MrBayes uses Markov chain Monte Carlo (MCMC) methods to estimate the posterior distribution...

BEAST
 Referenced in 30 articles
[sw12588]
 BEAST 2 uses Markov chain Monte Carlo (MCMC) to average over tree space, so that...

BRugs
 Referenced in 20 articles
[sw08183]
 BRugs: R interface to the OpenBUGS MCMC software. Fullyinteractive R interface to the OpenBUGS ... software for Bayesian analysis using MCMC sampling. Runs natively and stably...

MCMCglmm
 Referenced in 17 articles
[sw08302]
 package MCMCglmm: MCMC Generalised Linear Mixed Models. MCMC Generalised Linear Mixed Models...

Rtwalk
 Referenced in 16 articles
[sw14215]
 Implementation of the ’twalk’ MCMC Algorithm. The ’twalk’ is a generalpurpose MCMC...

spam
 Referenced in 22 articles
[sw07965]
 simple structure(s), (3) tailored for MCMC calculations within GMRF. (4) S3 and S4 like...

emcee
 Referenced in 13 articles
[sw20217]
 emcee: The MCMC Hammer. We introduce a stable, well tested Python implementation of the affine ... ensemble sampler for Markov chain Monte Carlo (MCMC) proposed by Goodman & Weare (2010). The code ... behind emcee has several advantages over traditional MCMC sampling methods and it has excellent performance...