notebooksCollection of (unfinished) notebooks
Stars: ✭ 13 (-75%)
cmdstanrCmdStanR: the R interface to CmdStan
Stars: ✭ 82 (+57.69%)
stan-vimA Vim plugin for the Stan probabilistic programming language.
Stars: ✭ 41 (-21.15%)
CausalQueriesBayesian inference from binary causal models
Stars: ✭ 20 (-61.54%)
natsclientNATS 2.x Client Library
Stars: ✭ 37 (-28.85%)
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 (-57.69%)
stan4bartUses Stan sampler and math library to semiparametrically fit linear and multilevel models with additive Bayesian Additive Regression Tree (BART) components.
Stars: ✭ 13 (-75%)
ubmsFit models to data from unmarked animals using Stan. Uses a similar interface to the R package 'unmarked', while providing the advantages of Bayesian inference and allowing estimation of random effects.
Stars: ✭ 27 (-48.08%)
stantargetsReproducible Bayesian data analysis pipelines with targets and cmdstanr
Stars: ✭ 31 (-40.38%)
stan-jaStanマニュアルの日本語への翻訳プロジェクト
Stars: ✭ 53 (+1.92%)
stanTuneRThis code uses the algebra solver in Stan (https://mc-stan.org/) to find the parameters of a distribution that produce a desired tail behavior.
Stars: ✭ 28 (-46.15%)
gsoc17-hhmmBayesian Hierarchical Hidden Markov Models applied to financial time series, a research replication project for Google Summer of Code 2017.
Stars: ✭ 102 (+96.15%)
walkerBayesian Generalized Linear Models with Time-Varying Coefficients
Stars: ✭ 38 (-26.92%)
bayesianBindings for Bayesian TidyModels
Stars: ✭ 33 (-36.54%)
covidestimBayesian nowcasting with adjustment for delayed and incomplete reporting to estimate COVID-19 infections in the United States
Stars: ✭ 20 (-61.54%)
geostanBayesian spatial analysis
Stars: ✭ 40 (-23.08%)
stan-distributionsA web app to visualize distributions in Stan. Uses Stan Math C++ compiled to Webassembly to evaluate the functions using actual Stan implementations. Uses d3.js for visualizations.
Stars: ✭ 30 (-42.31%)
metaBMABayesian Model Averaging for Random and Fixed Effects Meta-Analysis
Stars: ✭ 20 (-61.54%)
MathematicaStanA Mathematica package to interact with CmdStan
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Stancon talksMaterials from Stan conferences
Stars: ✭ 210 (+303.85%)
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 (+4086.54%)
Shinystanshinystan R package and ShinyStan GUI
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Stan.jlStan.jl illustrates the usage of the 'single method' packages, e.g. StanSample, StanOptimize, etc.
Stars: ✭ 163 (+213.46%)
Oreilly Intro To Predictive ClvRepo that contains the supporting material for O'Reilly Webinar "An Intro to Predictive Modeling for Customer Lifetime Value" on Feb 28, 2017
Stars: ✭ 153 (+194.23%)
Rstanbook『StanとRでベイズ統計モデリング』のサポートページです.
Stars: ✭ 152 (+192.31%)
Miscellaneous R CodeCode that might be useful to others for learning/demonstration purposes, specifically along the lines of modeling and various algorithms. Now almost entirely superseded by the models-by-example repo.
Stars: ✭ 146 (+180.77%)
ModelselectionTutorial on model assessment, model selection and inference after model selection
Stars: ✭ 139 (+167.31%)
Looloo R package for approximate leave-one-out cross-validation (LOO-CV) and Pareto smoothed importance sampling (PSIS)
Stars: ✭ 106 (+103.85%)
GgmcmcGraphical tools for analyzing Markov Chain Monte Carlo simulations from Bayesian inference
Stars: ✭ 95 (+82.69%)
Turn ClientSTUN & TURN client demo and api with python and C
Stars: ✭ 82 (+57.69%)
ProjpredProjection predictive variable selection
Stars: ✭ 76 (+46.15%)
MatlabstanMatlab interface to Stan, a package for Bayesian inference
Stars: ✭ 59 (+13.46%)
Bayes Vis Paper'Visualization in Bayesian workflow' by Gabry, Simpson, Vehtari, Betancourt, and Gelman. (JRSS discussion paper and code)
Stars: ✭ 47 (-9.62%)
Ssmodels In StanState space models (dynamic linear models, hidden Markov models) implemented in Stan.
Stars: ✭ 42 (-19.23%)
Epinow2Estimate Realtime Case Counts and Time-varying Epidemiological Parameters
Stars: ✭ 36 (-30.77%)
Cmdstan.jlCmdStan.jl v6 provides an alternative, older Julia wrapper to Stan's `cmdstan` executable.
Stars: ✭ 30 (-42.31%)
Covid19modelCode for modelling estimated deaths and cases for COVID19.
Stars: ✭ 913 (+1655.77%)
Pystan2PyStan, the Python interface to Stan
Stars: ✭ 915 (+1659.62%)
Brmsbrms R package for Bayesian generalized multivariate non-linear multilevel models using Stan
Stars: ✭ 825 (+1486.54%)
GpmicrobiomeA novel probabilistic approach to explicitly model overdispersion and sampling zeros in 16S rRNA sequencing data by considering the temporal correlation between nearby time points using Gaussian Processes
Stars: ✭ 5 (-90.38%)
Bda py demosBayesian Data Analysis demos for Python
Stars: ✭ 781 (+1401.92%)
RstanRStan, the R interface to Stan
Stars: ✭ 760 (+1361.54%)
TidybayesBayesian analysis + tidy data + geoms (R package)
Stars: ✭ 557 (+971.15%)
MathThe Stan Math Library is a C++ template library for automatic differentiation of any order using forward, reverse, and mixed modes. It includes a range of built-in functions for probabilistic modeling, linear algebra, and equation solving.
Stars: ✭ 494 (+850%)
Bda r demosBayesian Data Analysis demos for R
Stars: ✭ 409 (+686.54%)
OrbitA Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
Stars: ✭ 346 (+565.38%)
Rstanarmrstanarm R package for Bayesian applied regression modeling
Stars: ✭ 285 (+448.08%)
Bayesplotbayesplot R package for plotting Bayesian models
Stars: ✭ 276 (+430.77%)
EmbracingUncertaintyMaterial for AMLD 2020 workshop "Bayesian Inference: embracing uncertainty"
Stars: ✭ 23 (-55.77%)
Torstenlibrary of C++ functions that support applications of Stan in Pharmacometrics
Stars: ✭ 38 (-26.92%)
covidseirBayesian SEIR model to estimate the effects of social-distancing on COVID-19
Stars: ✭ 23 (-55.77%)