Alternatives and similar repositories for posteriordb

Users that are interested in posteriordb are comparing it to the libraries listed below

• roualdes / bridgestan
  BridgeStan provides efficient in-memory access through Python, Julia, and R to the methods of a Stan model.
  ☆106Updated 3 weeks ago
• betanalpha / mcmc_diagnostics
  Markov chain Monte Carlo general, and Hamiltonian Monte Carlo specific, diagnostics for Stan
  ☆89Updated 5 months ago
• pyro-ppl / brmp
  Bayesian Regression Models in Pyro
  ☆73Updated last year
• betanalpha / knitr_case_studies
  Inference case studies in knitr
  ☆171Updated 3 years ago
• gabriuma / basis_functions_approach_to_GP
  ☆56Updated 3 years ago
• elanmart / rust-pgbart
  ☆18Updated 2 years ago
• jgabry / bayes-workflow-book
  Source files for the book "Bayesian Workflow Using Stan"
  ☆97Updated 4 years ago
• stan-dev / cmdstanpy
  CmdStanPy is a lightweight interface to Stan for Python users which provides the necessary objects and functions to compile a Stan progra…
  ☆188Updated last week
• flatironinstitute / bayes-kit
  Bayesian inference and posterior analysis for Python
  ☆46Updated 2 years ago
• mattiasvillani / AdvBayesLearnCourse
  Course material for the PhD course in Advanced Bayesian Learning
  ☆60Updated 9 months ago
• bambinos / kulprit
  Kullback-Leibler projections for Bayesian model selection in Python
  ☆40Updated last week
• arviz-devs / preliz
  Exploring and eliciting probability distributions
  ☆160Updated 3 weeks ago
• pymc-devs / nutpie
  Python wrapper for nuts-rs
  ☆182Updated this week
• omaclaren / open-learning-material
  Some teaching material and other educational resources
  ☆41Updated 4 months ago
• abhiagwl / vistan
  A simple library to run variational inference on Stan models.
  ☆33Updated 2 years ago
• flatironinstitute / mcmc-monitor
  Monitor MCMC runs in the browser
  ☆38Updated last year
• jhuggins / viabel
  Efficient, lightweight variational inference and approximation bounds
  ☆46Updated 2 months ago
• betanalpha / stan_intro
  Draft introduction to probability and inference aimed at the Stan manual.
  ☆84Updated 9 years ago
• arviz-devs / simuk
  Simulation based calibration and generation of synthetic data.
  ☆56Updated last month
• bob-carpenter / prob-stats
  Probability and Statistics: a simulation-based introduction. An open-access book.
  ☆322Updated 2 years ago
• LedgerInvesting / bayesblend
  Easily combine predictions from multiple Bayesian models using techniques including (pseudo) Bayesian model averaging, hierarchical stack…
  ☆37Updated last week
• florence-bockting / elicito
  A python package for learning prior distributions based on expert knowledge
  ☆15Updated last month
• avehtari / modelselection
  Case studies on model assessment, model selection and inference after model selection
  ☆170Updated last year
• williambdean / conjugate
  Bayesian Conjugate Models in Python
  ☆33Updated last week
• betanalpha / quarto_chapters
  Book Chapter Drafts
  ☆37Updated last year
• syclik / stan-algorithms
  Reimplementation of Stan algorithms
  ☆19Updated 3 years ago
• sinhrks / stan-statespace
  Stan models for state space time series
  ☆146Updated 8 years ago
• justindomke / pangolin
  probabilistic programming focused on fun
  ☆49Updated this week
• pierrejacob / couplingsmontecarlo
  some scripts for the couplings enthusiasts!
  ☆32Updated 5 years ago
• stan-dev / cmdstan
  CmdStan, the command line interface to Stan
  ☆234Updated last week