Introducing the StataStan interface for fast, complex Bayesian modeling using Stan
Robert L. Grant
BayesCamp
Croydon, UK
[email protected]
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Bob Carpenter
Columbia University
New York, NY
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Daniel C. Furr
University of California at Berkeley
Berkeley, CA
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Andrew Gelman
Columbia University
New York, NY
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Abstract. In this article, we present StataStan, an interface that allows
simulation-based Bayesian inference in Stata via calls to Stan, the flexible,
open-source Bayesian inference engine. Stan is written in C++, and Stata users
can use the commands stan and windowsmonitor to run Stan programs
from within Stata. We provide a brief overview of Bayesian algorithms, details
of the commands available from Statistical Software Components, considerations
for users who are new to Stan, and a simple example. Stan uses a different
algorithm than bayesmh, BUGS, JAGS, SAS, and MLwiN. This algorithm
provides considerable improvements in efficiency and speed. In a companion
article, we give an extended comparison of StataStan and bayesmh in the
context of item response theory models.
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Robert L. Grant, Bob Carpenter, Daniel C. Furr, Andrew Gelman
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stan, windowsmonitor, StataStan, Bayesian, bayesmh, interface, shell commands, Stan
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