
BUGS
 Referenced in 365 articles
[sw07885]
 BUGS (Bayesian inference Using Gibbs Sampling) project is concerned with flexible software for the Bayesian...

Stan
 Referenced in 195 articles
[sw10200]
 probabilistic programming language implementing full Bayesian statistical inference with MCMC sampling (NUTS, HMC) and penalized...

bnlearn
 Referenced in 64 articles
[sw08265]
 network structure learning, parameter learning and inference. Bayesian network structure learning, parameter learning and inference ... parameter estimation (maximum likelihood and Bayesian) and inference, conditional probability queries and crossvalidation. Development...

MrBayes
 Referenced in 58 articles
[sw07715]
 MrBayes: Bayesian Inference of Phylogeny. MrBayes is a program for Bayesian inference and model choice...

OpenBUGS
 Referenced in 75 articles
[sw08316]
 software package for performing Bayesian inference Using Gibbs Sampling. The user specifies a statistical model...

RStan
 Referenced in 58 articles
[sw13990]
 probabilistic programming language that implements full Bayesian statistical inference ... Markov Chain Monte Carlo, rough Bayesian inference via variational approximation, and (optionally penalized) maximum likelihood...

BayesLogit
 Referenced in 44 articles
[sw09312]
 package BayesLogit: PolyaGamma Sampling. Bayesian inference for logistic models using PólyaGamma latent variables ... dataaugmentation strategy for fully Bayesian inference in models with binomial likelihoods. The approach appeals...

MultiNest
 Referenced in 39 articles
[sw10481]
 MultiNest: an efficient and robust Bayesian inference tool for cosmology and particle physics. We present ... nested sampling algorithm, called MultiNest. This Bayesian inference tool calculates the evidence, with an associated...

Mcmcpack
 Referenced in 50 articles
[sw07974]
 This package contains functions to perform Bayesian inference using posterior simulation for a number...

dlm
 Referenced in 29 articles
[sw04503]
 Maximum likelihood, Kalman filtering and smoothing, and Bayesian analysis of Normal linear State Space models ... have developed an R package, DIM, for inference and forecasting with dynamic linear models ... introduction, presenting basic notions in Bayesian inference. The basic elements of Bayesian analysis for linear ... much more elaborated one on Bayesian inference. The last chapter is on sequential Monte Carlo...

rstan
 Referenced in 28 articles
[sw16103]
 probabilistic programming language that implements full Bayesian statistical inference ... Markov Chain Monte Carlo, rough Bayesian inference via variational approximation, and (optionally penalized) maximum likelihood...

BioBayes
 Referenced in 25 articles
[sw08082]
 BioBayes: a software package for Bayesian inference in systems biology. MOTIVATION: There are several levels ... observed directly. The methods of Bayesian inference provide a consistent framework for modelling and predicting ... present a software package for applying the Bayesian inferential methodology to problems in systems biology...

ADVI
 Referenced in 26 articles
[sw34040]
 scalable technique for approximate Bayesian inference. Deriving variational inference algorithms requires tedious modelspecific calculations ... automatic differentiation variational inference (ADVI). The user only provides a Bayesian model and a dataset ... images. With ADVI we can use variational inference on any model we write in Stan...

Infer.NET
 Referenced in 27 articles
[sw07886]
 algorithms and statistical routines for performing Bayesian inference. It has applications in a wide variety...

bfa
 Referenced in 23 articles
[sw07430]
 justifications for using this likelihood in Bayesian inference. We propose new default priors...

brms
 Referenced in 22 articles
[sw19099]
 multilevel models using Stan for full Bayesian inference. A wide range of distributions and link...

LaplacesDemon
 Referenced in 15 articles
[sw11391]
 package LaplacesDemon: Complete Environment for Bayesian Inference. Provides a complete environment for Bayesian inference using...

BayesTree
 Referenced in 59 articles
[sw07995]
 Bayesian Additive Regression Trees. We develop a Bayesian “sumoftrees” model where each tree ... learner, and fitting and inference are accomplished via an iterative Bayesian backfitting MCMC algorithm that ... posterior. Effectively, BART is a nonparametric Bayesian regression approach which uses dimensionally adaptive random basis ... likelihood. This approach enables full posterior inference including point and interval estimates of the unknown...

PILCO
 Referenced in 20 articles
[sw34813]
 modeling of the dynamics and approximate Bayesian inference for policy evaluation and improvement...

abcrf
 Referenced in 12 articles
[sw21308]
 package abcrf: ABC random forests for Bayesian parameter inference. Approximate Bayesian computation (ABC) has grown ... into a standard methodology that manages Bayesian inference for models associated with intractable likelihood functions ... propose to conduct likelihoodfree Bayesian inferences about parameters with no prior selection...