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Stan for Bayesian Inference
June 24, 2015 @ 1:00 pm - 4:00 pm
Stan is an open-source, Bayesian inference tool with interfaces in R, Python, Matlab, Julia, Stata, and the command line. Users write statistical models in a high-level statistical language.
Description:
Stan is an open-source, Bayesian inference tool with interfaces in R, Python, Matlab, Julia, Stata, and the command line. Users write statistical models in a high-level statistical language.
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Stan is an open-source, Bayesian inference tool with interfaces in R, Python, Matlab, Julia, Stata, and the command line. Users write statistical models in a high-level statistical language. The default Bayesian inference algorithm is the no-U-turn sampler (NUTS), an auto-tuned version of Hamiltonian Monte Carlo. Stan was developed to address the speed and scalability issues of existing Bayesian inference tools.
The goal of the workshop is the practical application of Stan to different models.
Date: Wednesday, June 24, 2015
Time: 1 p.m. to 4 p.m. with coffee provided
Location: Donald Bren Hall, Room 3011
Instructor: Daniel Lee
Pre-requisites: Experience in Bayesian statistical modeling is recommended, but not required.