Fitting Bayesian regression models using the bayes prefix

Yulia Marchenko ()
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Yulia Marchenko: StataCorp LP

United Kingdom Stata Users' Group Meetings 2017 from Stata Users Group

Abstract: Stata 15 introduces the new bayes prefix for fitting Bayesian regression models more easily. It combines Bayesian features with Stata's intuitive and elegant specification of regression models. For example, you fit classical linear regression by using . regress y x1 x2 You can now fit Bayesian linear regression by using . bayes: regress y x1 x2 In addition to normal linear regression, the bayes prefix supports over 50 likelihood models including models for continuous, binary, ordinal, categorical, count, censored, survival outcomes, and more. All of Stata's Bayesian features are supported with the bayes prefix. In my presentation, I will demonstrate how to use the new bayes prefix to fit a variety of Bayesian regression models including survival and sample-selection models.

Date: 2017-09-14
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Persistent link: https://EconPapers.repec.org/RePEc:boc:usug17:13

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