Bda r demosBayesian Data Analysis demos for R
Stars: ✭ 409 (-47.63%)
Shinystanshinystan R package and ShinyStan GUI
Stars: ✭ 172 (-77.98%)
BayaderaHigh-performance Bayesian Data Analysis on the GPU in Clojure
Stars: ✭ 342 (-56.21%)
RstanRStan, the R interface to Stan
Stars: ✭ 760 (-2.69%)
Dbda PythonDoing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code
Stars: ✭ 502 (-35.72%)
DynamicHMCExamples.jlExamples for Bayesian inference using DynamicHMC.jl and related packages.
Stars: ✭ 33 (-95.77%)
LogDensityProblems.jlA common framework for implementing and using log densities for inference.
Stars: ✭ 26 (-96.67%)
Rstanarmrstanarm R package for Bayesian applied regression modeling
Stars: ✭ 285 (-63.51%)
StanStan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.
Stars: ✭ 2,177 (+178.75%)
Probabilistic ModelsCollection of probabilistic models and inference algorithms
Stars: ✭ 217 (-72.22%)
geostanBayesian spatial analysis
Stars: ✭ 40 (-94.88%)
GpstuffGPstuff - Gaussian process models for Bayesian analysis
Stars: ✭ 106 (-86.43%)
walkerBayesian Generalized Linear Models with Time-Varying Coefficients
Stars: ✭ 38 (-95.13%)
MultiBUGSMulti-core BUGS for fast Bayesian inference of large hierarchical models
Stars: ✭ 28 (-96.41%)
stan-jaStanマニュアルの日本語への翻訳プロジェクト
Stars: ✭ 53 (-93.21%)
GgmcmcGraphical tools for analyzing Markov Chain Monte Carlo simulations from Bayesian inference
Stars: ✭ 95 (-87.84%)
cmdstanrCmdStanR: the R interface to CmdStan
Stars: ✭ 82 (-89.5%)
BayesHMMFull Bayesian Inference for Hidden Markov Models
Stars: ✭ 35 (-95.52%)
Bayesplotbayesplot R package for plotting Bayesian models
Stars: ✭ 276 (-64.66%)
Rhat essRank-normalization, folding, and localization: An improved R-hat for assessing convergence of MCMC
Stars: ✭ 19 (-97.57%)
Rethinking PyroStatistical Rethinking with PyTorch and Pyro
Stars: ✭ 116 (-85.15%)
Pymc Example ProjectExample PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.
Stars: ✭ 90 (-88.48%)
ProjpredProjection predictive variable selection
Stars: ✭ 76 (-90.27%)
Bayesian Neural NetworksPytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more
Stars: ✭ 900 (+15.24%)
PygtcMake a sweet giant triangle confusogram (GTC) plot
Stars: ✭ 13 (-98.34%)
Beast2Bayesian Evolutionary Analysis by Sampling Trees
Stars: ✭ 156 (-80.03%)
Data science blogsA repository to keep track of all the code that I end up writing for my blog posts.
Stars: ✭ 139 (-82.2%)
Stan.jlStan.jl illustrates the usage of the 'single method' packages, e.g. StanSample, StanOptimize, etc.
Stars: ✭ 163 (-79.13%)
ExoplanetFast & scalable MCMC for all your exoplanet needs!
Stars: ✭ 122 (-84.38%)
McmcCollection of Monte Carlo (MC) and Markov Chain Monte Carlo (MCMC) algorithms applied on simple examples.
Stars: ✭ 218 (-72.09%)
metaBMABayesian Model Averaging for Random and Fixed Effects Meta-Analysis
Stars: ✭ 20 (-97.44%)
SCICoNESingle-cell copy number calling and event history reconstruction.
Stars: ✭ 20 (-97.44%)
pysgmcmcBayesian Deep Learning with Stochastic Gradient MCMC Methods
Stars: ✭ 31 (-96.03%)
blangSDKBlang's software development kit
Stars: ✭ 21 (-97.31%)
covidestimBayesian nowcasting with adjustment for delayed and incomplete reporting to estimate COVID-19 infections in the United States
Stars: ✭ 20 (-97.44%)
Bridge.jlA statistical toolbox for diffusion processes and stochastic differential equations. Named after the Brownian Bridge.
Stars: ✭ 99 (-87.32%)
bayesianBindings for Bayesian TidyModels
Stars: ✭ 33 (-95.77%)
webmc3A web interface for exploring PyMC3 traces
Stars: ✭ 46 (-94.11%)
go-topicsLatent Dirichlet Allocation
Stars: ✭ 23 (-97.06%)
anestheticNested Sampling post-processing and plotting
Stars: ✭ 34 (-95.65%)
KissABC.jlPure julia implementation of Multiple Affine Invariant Sampling for efficient Approximate Bayesian Computation
Stars: ✭ 28 (-96.41%)
lgprR-package for interpretable nonparametric modeling of longitudinal data using additive Gaussian processes. Contains functionality for inferring covariate effects and assessing covariate relevances. Various models can be specified using a convenient formula syntax.
Stars: ✭ 22 (-97.18%)
BirchA probabilistic programming language that combines automatic differentiation, automatic marginalization, and automatic conditioning within Monte Carlo methods.
Stars: ✭ 80 (-89.76%)
stan4bartUses Stan sampler and math library to semiparametrically fit linear and multilevel models with additive Bayesian Additive Regression Tree (BART) components.
Stars: ✭ 13 (-98.34%)
SMC.jlSequential Monte Carlo algorithm for approximation of posterior distributions.
Stars: ✭ 53 (-93.21%)
EmbracingUncertaintyMaterial for AMLD 2020 workshop "Bayesian Inference: embracing uncertainty"
Stars: ✭ 23 (-97.06%)
BASBAS R package https://merliseclyde.github.io/BAS/
Stars: ✭ 36 (-95.39%)
Torstenlibrary of C++ functions that support applications of Stan in Pharmacometrics
Stars: ✭ 38 (-95.13%)
BayesianTutorialsImplementing MCMC sampling from scratch in R for various Bayesian models
Stars: ✭ 75 (-90.4%)
OrbitA Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
Stars: ✭ 346 (-55.7%)
Vae cfVariational autoencoders for collaborative filtering
Stars: ✭ 386 (-50.58%)