
BayesDA
 Referenced in 815 articles
[sw11008]
 BayesDA: Functions and Datasets for the book ”Bayesian Data Analysis” Functions for Bayesian Data Analysis ... with datasets from the book ”Bayesian data Analysis (second edition)” by Gelman, Carlin, Stern...

BUGS
 Referenced in 299 articles
[sw07885]
 BUGS (Bayesian inference Using Gibbs Sampling) project is concerned with flexible software for the Bayesian...

spBayes
 Referenced in 254 articles
[sw10160]
 geostatistical data are often best analyzed with Bayesian hierarchical models. Unfortunately, fitting such models involves...

tsbridge
 Referenced in 146 articles
[sw12354]
 tsbridge: Calculate normalising constants for Bayesian time series models. The tsbridge package contains a collection ... probabilities for a variety of time series Bayesian models, where parameters are estimated using BUGS...

mclust
 Referenced in 195 articles
[sw00563]
 Based Clustering, Classification, and Density Estimation, including Bayesian regularization...

JAGS
 Referenced in 136 articles
[sw08040]
 program for analysis of Bayesian hierarchical models using Markov Chain Monte Carlo (MCMC) simulation ... plaftorm for experimentation with ideas in Bayesian modelling. JAGS is licensed under the GNU General...

Stan
 Referenced in 102 articles
[sw10200]
 probabilistic programming language implementing full Bayesian statistical inference with MCMC sampling (NUTS, HMC) and penalized...

AutoClass
 Referenced in 68 articles
[sw26092]
 Autoclass  A Bayesian Approach to Classification. We describe a Bayesian approach to the unsupervised discovery...

PMTK
 Referenced in 91 articles
[sw14689]
 framework encompassing machine learning, graphical models, and Bayesian statistics (hence the logo). (Some methods from...

BayesTree
 Referenced in 50 articles
[sw07995]
 BayesTree: Bayesian Methods for Tree Based Models: Implementation of BART: Bayesian Additive Regression Trees ... develop a Bayesian “sumoftrees” model where each tree is constrained by a regularization ... inference are accomplished via an iterative Bayesian backfitting MCMC algorithm that generates samples from ... posterior. Effectively, BART is a nonparametric Bayesian regression approach which uses dimensionally adaptive random basis...

DPpackage
 Referenced in 47 articles
[sw10495]
 DPpackage: Bayesian Semi and Nonparametric Modeling in R. Data analysis sometimes requires the relaxation ... specification of the probability model. In the Bayesian context, this is accomplished by placing ... programs for the implementation of some Bayesian nonparametric and semiparametric models in R, DPpackage. Currently...

PicHunter
 Referenced in 53 articles
[sw14896]
 PicHunter: Bayesian relevance feedback for image retrieval. This paper describes PicHunter, an image retrieval system ... goal image. To accomplish this, PicHunter uses Bayesian learning based on a probabilistic model...

boa
 Referenced in 72 articles
[sw04493]
 package boa: Bayesian Output Analysis Program (BOA) for MCMC. A menudriven program and library...

bayesm
 Referenced in 43 articles
[sw06787]
 Teaching Bayesian statistics to marketing and business students. We discuss our experiences teaching Bayesian statistics ... course that emphasizes the value of the Bayesian approach to solving nontrivial problems. The success...

OpenBUGS
 Referenced in 62 articles
[sw08316]
 BUGS is a software package for performing Bayesian inference Using Gibbs Sampling. The user specifies...

bvarsv
 Referenced in 62 articles
[sw11023]
 bvarsv: Bayesian Analysis of a Vector Autoregressive Model with Stochastic Volatility and TimeVarying Parameters...

HdBCS
 Referenced in 59 articles
[sw29884]
 HdBCS  Highdimensional Bayesian Covariance Selection. This site provides C++ code software implementing...

Amos
 Referenced in 56 articles
[sw06515]
 easily compare, confirm and refine models. Uses Bayesian analysis—to improve estimates of model parameters...

bnlearn
 Referenced in 34 articles
[sw08265]
 package bnlearn: Bayesian network structure learning, parameter learning and inference. Bayesian network structure learning, parameter ... support for parameter estimation (maximum likelihood and Bayesian) and inference, conditional probability queries and cross...

dlm
 Referenced in 26 articles
[sw04503]
 package dlm: Bayesian and Likelihood Analysis of Dynamic Linear Models. Maximum likelihood, Kalman filtering ... smoothing, and Bayesian analysis of Normal linear State Space models, also known as Dynamic Linear ... gives an introduction, presenting basic notions in Bayesian inference. The basic elements of Bayesian analysis ... much more elaborated one on Bayesian inference. The last chapter is on sequential Monte Carlo...