• BayesLogit

  • Referenced in 44 articles [sw09312]
  • package BayesLogit: PolyaGamma Sampling. Bayesian inference for logistic models using Pólya-Gamma latent variables ... data-augmentation strategy for fully Bayesian inference in models with binomial likelihoods. The approach appeals...
  • stochvol

  • Referenced in 16 articles [sw19383]
  • Volatility (SV) Models. Efficient algorithms for fully Bayesian estimation of stochastic volatility (SV) models...
  • ESS++

  • Referenced in 4 articles [sw24089]
  • Bayesian variable selection for linear regression using evolutionary Monte Carlo ... implementation of a fully Bayesian variable selection approach for single and multiple response linear regression...
  • Monomvn

  • Referenced in 10 articles [sw08173]
  • arbitrary missingness patterns. A fully functional standalone interface to the Bayesian lasso (from Park & Casella...
  • BRugs

  • Referenced in 22 articles [sw08183]
  • MCMC software. Fully-interactive R interface to the OpenBUGS software for Bayesian analysis using MCMC...
  • BayesNSGP

  • Referenced in 2 articles [sw30769]
  • Enables off-the-shelf functionality for fully Bayesian, nonstationary Gaussian process modeling. The approach...
  • TauREx

  • Referenced in 2 articles [sw28453]
  • Retrieval for Exoplanets) is a fully bayesian inverse atmospheric retrieval framework. TauREx is a very...
  • MFclass

  • Referenced in 2 articles [sw34570]
  • Gaussian process priors. We adopt a fully Bayesian treatment for the hyper-parameters...
  • Graph_sampler

  • Referenced in 1 article [sw20652]
  • Graph_sampler: a simple tool for fully Bayesian analyses of DAG-models. Bayesian networks ... Graph_sampler uses a fully Bayesian approach in which the marginal likelihood of the data...
  • factorstochvol

  • Referenced in 1 article [sw31446]
  • package factorstochvol: Bayesian Estimation of (Sparse) Latent Factor Stochastic Volatility Models. Markov ... chain Monte Carlo (MCMC) sampler for fully Bayesian estimation of latent factor stochastic volatility models...
  • shrinkTVP

  • Referenced in 1 article [sw29787]
  • package shrinkTVP: Efficient Bayesian Inference for Time-Varying Parameter Models with Shrinkage. Efficient Markov ... chain Monte Carlo (MCMC) algorithms for fully Bayesian estimation of time-varying parameter models with...
  • HHSIM

  • Referenced in 1 article [sw15448]
  • distribution of unit-specific parameters. The Bayesian approach provides a powerful way to structure models ... scenarios and compare empirical Bayes and fully Bayesian approaches to model the population distribution...
  • SCORIGHT

  • Referenced in 1 article [sw16979]
  • estimation is accomplished within a fully Bayesian framework using Markov chain Monte Carlo procedures, which...
  • SIMMAP

  • Referenced in 1 article [sw21252]
  • Analyses can be performed using a fully Bayesian approach that is not reliant on considering...
  • StarBEAST2

  • Referenced in 1 article [sw29665]
  • accurate estimates of substitution rates. Fully Bayesian multispecies coalescent (MSC) methods like *BEAST estimate species...
  • pacbpred

  • Referenced in 4 articles [sw07805]
  • method is fully described in Guedj and Alquier (2013), ’PAC-Bayesian Estimation and Prediction...
  • MultiNest

  • Referenced in 36 articles [sw10481]
  • multimodal nested sampling algorithm, called MultiNest. This Bayesian inference tool calculates the evidence, with ... dark energy. The MultiNest software, which is fully parallelized using MPI and includes an interface...
  • BACCO

  • Referenced in 8 articles [sw10536]
  • bundle of R routines for carrying out Bayesian analysis of computer code output. The bundle ... respectively. The bundle is self-contained and fully documented R code, and includes ... functions. Package emulator carries out Bayesian emulation of computer code output; package calibrator allows...
  • BDAGL

  • Referenced in 1 article [sw14322]
  • package (pronounced ”be-daggle”) supports Bayesian inference about (fully observed) DAG (directed acyclic graph) structures...
  • AutoClass@IJM

  • Referenced in 2 articles [sw25643]
  • applied studies have shown that unsupervised Bayesian classification systems are of particular relevance for biological ... studies. However, these systems have not yet fully reached the biological community mainly because there ... freely available dedicated computer programs, and Bayesian clustering algorithms are known to be time consuming...