
WinBUGS
 Referenced in 776 articles
[sw04492]
 BUGS project, which aims to make practical MCMC methods available to applied statisticians. WinBUGS...

CODA
 Referenced in 359 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...

GMRFLib
 Referenced in 338 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...

spBayes
 Referenced in 394 articles
[sw10160]
 involves computationally intensive Markov chain Monte Carlo (MCMC) methods whose efficiency depends upon the specific...

BUGS
 Referenced in 390 articles
[sw07885]
 statistical models using Markov chain Monte Carlo (MCMC) methods. The project began...

Stan
 Referenced in 314 articles
[sw10200]
 language implementing full Bayesian statistical inference with MCMC sampling (NUTS, HMC) and penalized maximum likelihood...

JAGS
 Referenced in 278 articles
[sw08040]
 hierarchical models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. JAGS...

rjags
 Referenced in 69 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...

MLwiN
 Referenced in 108 articles
[sw04837]
 likelihood estimation and Markov Chain Monte Carlo (MCMC) methods. MLwiN is based on an earlier...

BartPy
 Referenced in 99 articles
[sw40584]
 accomplished via an iterative Bayesian backfitting MCMC algorithm that generates samples from a posterior. Effectively...

boa
 Referenced in 93 articles
[sw04493]
 Bayesian Output Analysis Program (BOA) for MCMC. A menudriven program and library of functions...

emcee
 Referenced in 57 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...

Mcmcpack
 Referenced in 63 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...

OpenBUGS
 Referenced in 84 articles
[sw08316]
 expert system’, which determines an appropriate MCMC (Markov chain Monte Carlo) scheme (based...

BayesTree
 Referenced in 64 articles
[sw07995]
 accomplished via an iterative Bayesian backfitting MCMC algorithm that generates samples from a posterior. Effectively...

MrBayes
 Referenced in 62 articles
[sw07715]
 models. MrBayes uses Markov chain Monte Carlo (MCMC) methods to estimate the posterior distribution...

BEAST
 Referenced in 60 articles
[sw12588]
 BEAST 2 uses Markov chain Monte Carlo (MCMC) to average over tree space, so that...

SSS
 Referenced in 38 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...

MCMCglmm
 Referenced in 36 articles
[sw08302]
 package MCMCglmm: MCMC Generalised Linear Mixed Models. MCMC Generalised Linear Mixed Models...

CosmoMC
 Referenced in 43 articles
[sw16206]
 Fortran 2008 MarkovChain MonteCarlo (MCMC) engine for exploring cosmological parameter space, together with...