671 Open source projects that are alternatives of or similar to Rstanarm

shinystan R package and ShinyStan GUI

Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.

RStan, the R interface to Stan

Rank-normalization, folding, and localization: An improved R-hat for assessing convergence of MCMC

A collection of Bayesian data analysis recipes using PyMC3

Bayesian spatial analysis

Projection predictive variable selection

Statistical Rethinking with PyTorch and Pyro

Implementation of robust dynamic Hamiltonian Monte Carlo methods (NUTS) in Julia.

Bayesian Data Analysis demos for Python

How to do Bayesian statistical modelling using numpy and PyMC3

Bayesian Data Analysis demos for R

loo R package for approximate leave-one-out cross-validation (LOO-CV) and Pareto smoothed importance sampling (PSIS)

A common framework for implementing and using log densities for inference.

High-performance Bayesian Data Analysis on the GPU in Clojure

C++ template library for probabilistic programming

A Python package for building Bayesian models with TensorFlow or PyTorch

Statistical Rethinking course in pymc3

bayesplot R package for plotting Bayesian models

Solutions of practice problems from the Richard McElreath's "Statistical Rethinking" book.

Stanマニュアルの日本語への翻訳プロジェクト

Examples for Bayesian inference using DynamicHMC.jl and related packages.

brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan

Bayesian analysis + tidy data + geoms (R package)

A high-level Bayesian analysis API written in Python

CmdStanR: the R interface to CmdStan

A Bayesian Analysis Toolkit in Julia

Bayesian inference with probabilistic programming.

Example PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.

ParaMonte: Plain Powerful Parallel Monte Carlo and MCMC Library for Python, MATLAB, Fortran, C++, C.

PyMC3 codes of Lee and Wagenmakers' Bayesian Cognitive Modeling - A Pratical Course

GPstuff - Gaussian process models for Bayesian analysis

The base NIMBLE package for R

Personal project to compare hierarchical linear regression in PyMC3 and PyStan, as presented at http://pydata.org/london2016/schedule/presentation/30/ video: https://www.youtube.com/watch?v=Jb9eklfbDyg

Deep universal probabilistic programming with Python and PyTorch

Bayesian Coherent Point Drift (BCPD/BCPD++); Source Code Available

Expressions and dataframes with statistical details 📉 📜🔣✅

ELFI - Engine for Likelihood-Free Inference

Probabilistic programming via source rewriting

Collection of probabilistic models and inference algorithms

Separating Normalizing Flows code from Pyro and improving API

Development of the R package 'Luminescence'

Transformations to contrained variables from ℝⁿ.

PyMC3 educational resources

Statistical Rethinking (2nd Ed) with Tensorflow Probability

Bayesian Model Averaging for Random and Fixed Effects Meta-Analysis

Bayesian SEIR model to estimate the effects of social-distancing on COVID-19

Bindings for Bayesian TidyModels

Bayesian nowcasting with adjustment for delayed and incomplete reporting to estimate COVID-19 infections in the United States

Full Bayesian Inference for Hidden Markov Models

Bayesian Generalized Linear Models with Time-Varying Coefficients

Simultaneous Localization and Mapping(SLAM) also gives you a way to track the location of a robot in the world in real-time and identify the locations of landmarks such as buildings, trees, rocks, and other world features.

Material for a Bayesian statistics workshop

Pure julia implementation of Multiple Affine Invariant Sampling for efficient Approximate Bayesian Computation

The Trendiness of Trends

Blang's software development kit

Multi-core BUGS for fast Bayesian inference of large hierarchical models

Reproducible Bayesian data analysis pipelines with targets and cmdstanr

Data-driven Network-based Bayesian Inference of Drivers

🎓 Uni-Bonn Decision Analysis graduate course, lectures and materials