• JAGS

  • Referenced in 200 articles [sw08040]
  • JAGS is Just Another Gibbs Sampler. It is a program for analysis of Bayesian hierarchical ... models using Markov Chain Monte Carlo (MCMC) simulation not wholly unlike BUGS. JAGS was written ... write their own functions, distributions and samplers. (3) To be a plaftorm for experimentation with...
  • Rtwalk

  • Referenced in 22 articles [sw14215]
  • walk’ is a general-purpose MCMC sampler for arbitrary continuous distributions that requires no tuning...
  • OpenBUGS

  • Referenced in 71 articles [sw08316]
  • appropriate MCMC (Markov chain Monte Carlo) scheme (based on the Gibbs sampler) for analysing...
  • emcee

  • Referenced in 29 articles [sw20217]
  • emcee: The MCMC Hammer. We introduce a stable, well tested Python implementation ... affine-invariant ensemble sampler for Markov chain Monte Carlo (MCMC) proposed by Goodman & Weare...
  • MfUSampler

  • Referenced in 4 articles [sw20444]
  • package MfUSampler. Multivariate-from-Univariate (MfU) MCMC Sampler. Convenience functions for multivariate MCMC using univariate...
  • RaschSampler

  • Referenced in 3 articles [sw25840]
  • package RaschSampler: Rasch Sampler. MCMC based sampling of binary matrices with fixed margins as used...
  • HYDRA

  • Referenced in 3 articles [sw10159]
  • implements the logic of standard MCMC samplers within a framework designed to be easy...
  • SamplerCompare

  • Referenced in 2 articles [sw10539]
  • performance of Markov chain Monte Carlo (MCMC) samplers. It samples from a collection of distributions ... with a collection of MCMC methods over a range of tuning parameters. Then, using ... with a collection of predefined distributions and samplers and provides R and C interfaces...
  • mcmcabn

  • Referenced in 1 article [sw31038]
  • mcmcabn: Flexible Implementation of a Structural MCMC Sampler for DAGs. Flexible implementation of a structural ... MCMC sampler for Directed Acyclic Graphs (DAGs). It supports the new edge reversal move from ... over structures or nuisance dependencies. Structural MCMC seems a very elegant and natural...
  • mcgibbsit

  • Referenced in 1 article [sw24887]
  • necessarily independent) MCMC samplers. It combines the estimate error-bounding approach of the Raftery...
  • zic

  • Referenced in 1 article [sw35800]
  • selection (SVS) is also considered. All MCMC samplers are coded in C++ for improved efficiency...
  • factorstochvol

  • Referenced in 1 article [sw31446]
  • Volatility Models. Markov chain Monte Carlo (MCMC) sampler for fully Bayesian estimation of latent factor...
  • PyMCMC

  • Referenced in 1 article [sw24402]
  • that aids in the construction of MCMC samplers and helps to substantially reduce the likelihood...
  • PyAstrOFit

  • Referenced in 1 article [sw30805]
  • approach, written in Python 2.7. The MCMC sampler makes direct use of emcee (Foreman-Mackey...
  • CPNest

  • Referenced in 1 article [sw36229]
  • implementation is based on an ensemble MCMC sampler which can use multiple cores to parallelise...
  • PyMultiNest

  • Referenced in 1 article [sw28457]
  • arxiv.org/abs/0809.3437, or in a classic MCMC sampler, http://apemost.sf.net/ ). Recently, MultiNest added Importance Nested...
  • t-walk

  • Referenced in 20 articles [sw14214]
  • algorithms and software difficult); it is an MCMC that does not required tuning. However ... well in some examples and fine tuned samplers to specific objective densities should perform better...
  • runjags

  • Referenced in 14 articles [sw10688]
  • parallel computing methods and additional distributions for MCMC models in JAGS. This package provides high ... level interface utilities for Just Another Gibbs Sampler (JAGS). The primary functions facilitate running parallel...
  • CosmoMC

  • Referenced in 18 articles [sw16206]
  • Fortran 2008 Markov-Chain Monte-Carlo (MCMC) engine for exploring cosmological parameter space, together with ... also be compiled as a generic sampler without using any cosmology codes...