162 results for “topic:bayesian-data-analysis”
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.
Bayesian Data Analysis course at Aalto
RStan, the R interface to Stan
Bayesian Data Analysis demos for Python
Python/PyMC3 port of the examples in " Statistical Rethinking A Bayesian Course with Examples in R and Stan" by Richard McElreath
Bayesian analysis + tidy data + geoms (R package)
Doing Bayesian Data Analysis, 2nd Edition (Kruschke, 2015): Python/PyMC3 code
How to do Bayesian statistical modelling using numpy and PyMC3
Bayesian Data Analysis demos for R
A collection of Bayesian data analysis recipes using PyMC3
rstanarm R package for Bayesian applied regression modeling
High-performance Bayesian Data Analysis on the GPU in Clojure
shinystan R package and ShinyStan GUI
Statistical Rethinking with PyTorch and Pyro
Exploring and eliciting probability distributions
loo R package for approximate leave-one-out cross-validation (LOO-CV) and Pareto smoothed importance sampling (PSIS)
Graphical tools for analyzing Markov Chain Monte Carlo simulations from Bayesian inference
Example PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.
Introduction to Bayesian Data Analysis for Cognitive Science by Nicenboim, Schad, Vasishth
:no_entry_sign: :leftwards_arrow_with_hook: A document that introduces Bayesian data analysis.
Solutions and workflow for the Bayesian Statistics The Fun Way book in Python
priorsense: an R package for prior diagnostics and sensitivity
Doing Bayesian statistics in Python!
'Visualization in Bayesian workflow' by Gabry, Simpson, Vehtari, Betancourt, and Gelman. (JRSS discussion paper and code)
Stanマニュアルの日本語への翻訳プロジェクト
Bayesian Data Analysis demos for Matlab/Octave
Solutions of practice problems from the Richard McElreath's "Statistical Rethinking" book.
Bayesian Cost Effectiveness Analysis. Given the results of a Bayesian model (possibly based on MCMC) in the form of simulations from the posterior distributions of suitable variables of costs and clinical benefits for two or more interventions, produces a health economic evaluation. Compares one of the interventions (the "reference") to the others ("comparators"). Produces many summary and plots to analyse the results
Tools for Developing R Packages Interfacing with Stan
Reproducing plots of Bayesian Data Analysis (Gelman et al, 3rd Edition) in Python