• Stan

  • Referenced in 302 articles [sw10200]
  • full Bayesian statistical inference with MCMC sampling (NUTS, HMC) and penalized maximum likelihood estimation with...
  • glmmAK

  • Referenced in 28 articles [sw13218]
  • regression (log-linear model). Secondly, Bayesian estimation based on MCMC in the logistic and Poisson...
  • MrBayes

  • Referenced in 62 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 26 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 25 articles [sw19383]
  • fully Bayesian estimation of stochastic volatility (SV) models via Markov chain Monte Carlo (MCMC) methods...
  • BayesPostEst

  • Referenced in 3 articles [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...
  • BartPy

  • Referenced in 99 articles [sw40584]
  • 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...
  • BEAST

  • Referenced in 60 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...
  • BayesTree

  • Referenced in 64 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...
  • dclone

  • Referenced in 15 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...
  • BayesSpec

  • Referenced in 19 articles [sw38471]
  • methods for spectral analysis using the Bayesian framework. It includes functions for modelling spectrum ... plotting and output estimates. There is segmentation capability with RJ MCMC (Reversible Jump Markov Chain...
  • spatcounts

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

  • Referenced in 3 articles [sw31446]
  • Markov chain Monte Carlo (MCMC) sampler for fully Bayesian estimation of latent factor stochastic volatility...
  • binspp

  • Referenced in 1 article [sw42220]
  • Neyman-Scott Point Processes. The Bayesian MCMC estimation of parameters for Thomas-type cluster point ... package also allows for the Bayesian MCMC algorithm for the homogeneous generalized Thomas process...
  • shrinkTVP

  • Referenced in 3 articles [sw29787]
  • Markov chain Monte Carlo (MCMC) algorithms for fully Bayesian estimation of time-varying parameter models...
  • reglogit

  • Referenced in 10 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...
  • GEMMA

  • Referenced in 5 articles [sw23999]
  • Bayesian sparse linear mixed model (BSLMM) using Markov chain Monte Carlo (MCMC) for estimating...
  • 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...
  • bcp

  • Referenced in 11 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...