Introduction to Bayesian Analysis Using Stata

Chuck Huber ()
Additional contact information
Chuck Huber: StataCorp

Canadian Stata Users' Group Meetings 2017 from Stata Users Group

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.

Date: 2017-09-20
References: Add references at CitEc
Citations:

Downloads: (external link)
http://repec.org/csug2017/Canada17_Huber.pptx presentation materials (application/x-ms-powerpoint)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:boc:csug17:14

Access Statistics for this paper

More papers in Canadian Stata Users' Group Meetings 2017 from Stata Users Group Contact information at EDIRC.
Bibliographic data for series maintained by Christopher F Baum ().