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Introduction to Bayesian Analysis Using Stata

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  • Chuck Huber

    (StataCorp)

Abstract

Bayesian analysis has become a popular tool for many statistical applications. Yet many statisticians have little training in the theory of Bayesian analysis and software used to fit Bayesian models. This talk will provide an intuitive introduction to the concepts of Bayesian analysis and demonstrate how to fit Bayesian models using Stata. No prior knowledge of Bayesian analysis is necessary and specific topics will include the relationship between likelihood functions, prior, and posterior distributions, Markov Chain Monte Carlo (MCMC) using the Metropolis-Hastings algorithm, and how to use Stata's graphical user interface and command syntax to fit Bayesian models.

Suggested Citation

  • Chuck Huber, 2017. "Introduction to Bayesian Analysis Using Stata," Canadian Stata Users' Group Meetings 2017 14, Stata Users Group.
    • Handle: RePEc:boc:csug17:14
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    File URL: http://repec.org/csug2017/Canada17_Huber.pptx
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