• Stan

  • Referenced in 174 articles [sw10200]
  • full Bayesian statistical inference with MCMC sampling (NUTS, HMC) and penalized maximum likelihood estimation with...
  • glmmAK

  • Referenced in 25 articles [sw13218]
  • regression (log-linear model). Secondly, Bayesian estimation based on MCMC in the logistic and Poisson...
  • MrBayes

  • Referenced in 49 articles [sw07715]
  • Phylogeny. MrBayes is a program for Bayesian inference and model choice across a wide range ... uses Markov chain Monte Carlo (MCMC) methods to estimate the posterior distribution of model parameters...
  • Label.switching

  • Referenced in 18 articles [sw14745]
  • package label.switching: Relabelling MCMC Outputs of Mixture Models. The Bayesian estimation of mixture models ... from the label switching phenomenon, making the MCMC output non-identifiable. This package...
  • stochvol

  • Referenced in 16 articles [sw19383]
  • fully Bayesian estimation of stochastic volatility (SV) models via Markov chain Monte Carlo (MCMC) methods...
  • BEAST

  • Referenced in 44 articles [sw12588]
  • platform program for Bayesian phylogenetic analysis of molecular sequences. It estimates rooted, time-measured phylogenies ... BEAST 2 uses Markov chain Monte Carlo (MCMC) to average over tree space, so that...
  • ABCtoolbox

  • Referenced in 11 articles [sw08813]
  • perform Approximate Bayesian Computation (ABC) estimations using various recently published algorithms including MCMC without likelihood...
  • BayesPostEst

  • Referenced in 1 article [sw31515]
  • MCMC Estimation. An implementation of functions to generate and plot postestimation quantities after estimating Bayesian ... chain Monte Carlo (MCMC). Functionality includes the estimation of the Precision-Recall curves (see Beger ... used with MCMC output generated by any Bayesian estimation tool including ’JAGS’, ’BUGS’, ’MCMCpack...
  • BayesTree

  • Referenced in 58 articles [sw07995]
  • MCMC algorithm that generates samples from a posterior. Effectively, BART is a nonparametric Bayesian regression ... full posterior inference including point and interval estimates of the unknown regression function as well...
  • spatcounts

  • Referenced in 6 articles [sw13743]
  • develop and implement MCMC algorithms in $R$ for Bayesian estimation. The corresponding R library `spatcounts...
  • dclone

  • Referenced in 12 articles [sw23656]
  • maximum likelihood estimating procedures for complex models using data cloning and Bayesian Markov chain Monte ... Sequential and parallel MCMC support for ’JAGS’, ’WinBUGS’ and ’OpenBUGS...
  • reglogit

  • Referenced in 8 articles [sw14464]
  • Gibbs sampling. The package implements subtly different MCMC schemes with varying efficiency depending ... desired estimator (regularized maximum likelihood, or Bayesian maximum a posteriori/posterior mean, etc.) through a unified...
  • PLMIX

  • Referenced in 4 articles [sw19806]
  • Bayesian framework. It provides MAP point estimates via EM algorithm and posterior MCMC simulations ... special case of the noninformative Bayesian analysis with vague priors...
  • GEMMA

  • Referenced in 4 articles [sw23999]
  • Bayesian sparse linear mixed model (BSLMM) using Markov chain Monte Carlo (MCMC) for estimating...
  • factorstochvol

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

  • Referenced in 3 articles [sw21115]
  • MCMC) posterior samples to estimate a posterior density given the full data set. Recent Bayesian ... Markov chain Monto Carlo (MCMC) methods have been developed for big data sets that...
  • pacbpred

  • Referenced in 4 articles [sw07805]
  • perform estimation and prediction in high-dimensional additive models, using a sparse PAC-Bayesian point ... MCMC algorithm. The method is fully described in Guedj and Alquier (2013), ’PAC-Bayesian Estimation...
  • bcp

  • Referenced in 9 articles [sw14696]
  • package bcp: Bayesian Analysis of Change Point Problems. Provides an implementation of the Barry ... this allows estimation of change point models with multivariate responses. Parallel MCMC, previously available...
  • BayesCAT

  • Referenced in 1 article [sw29694]
  • estimating phylogeny and sequence alignment which improves estimates from the traditional approach by accounting ... size. We employ a Bayesian approach using MCMC to estimate the joint posterior distribution ... complete history of indel events makes our MCMC approach more challenging, but it enables ... real data. Software named BayesCAT (Bayesian Co-estimation of Alignment and Tree) is available...
  • blasso

  • Referenced in 13 articles [sw06769]
  • This article broadens the scope of the Bayesian connection by providing a complete characterization ... prior distributions that generate the elastic net estimate as the posterior mode. The resulting model ... Monte Carlo (MCMC) methods. Uncertainty about model specification is addressed from a Bayesian perspective...