[Forum SIS] seminar: "Revisiting the Gelman-Rubin Diagnostic", Dootika Vats November 9

[Umberto Picchini]

You are welcome to the next Statistics seminar at Dept of Mathematical 
Sciences at Chalmers and Göteborg University.

We are very glad to have, on Tuesday 9  November,​Dootika Vats (Indian 
Institute of Technology, Kanpur) who will talk of:

/"Revisiting the Gelman-Rubin Diagnostic"/

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About the speaker: Dootika Vats <https://dvats.github.io/> is Assistan 
Professor at the Indian Instute of Technology in Kanpur. She is the 2021 
recipient of the ISBA "Blackwell-Rosenbluth Award". She works in the 
general area of Bayesian computation and specifically focus on Markov 
chain Monte Carlo algorithms.

****Dootika VatsAbstract *Gelman and Rubin's (1992) convergence 
diagnostic is one of the most popular methods for terminating a Markov 
chain Monte Carlo (MCMC) sampler. Since the seminal paper, researchers 
have developed sophisticated methods of variance estimation for Monte 
Carlo averages. We show that this class of estimators find immediate use 
in the Gelman-Rubin statistic, a connection not established in the 
literature before. We incorporate these estimators to upgrade both the 
univariate and multivariate Gelman-Rubin statistics, leading to 
increased stability in MCMC termination time. An immediate advantage is 
that our new Gelman-Rubin statistic can also be calculated for a single 
chain. In addition, we establish a relationship between the Gelman-Rubin 
statistic and effective sample size. Leveraging this relationship, we 
develop a principled cutoff criterion for the Gelman-Rubin statistic. 
Finally, we demonstrate the utility of our improved diagnostic via an 
example. This work is joint with Christina Knudson, University of St. 
Thomas, Minnesota.** *
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*Feel free to spread this announcement in your network.*
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*Where*: *room MVL15 and zoom* (physical attendance is very welcome)
https://chalmers.zoom.us/j/67043486361
Password: 946764
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*When*: Tuesday 9 November at 14.15-15.15 (Swedish time).
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Umberto Picchini, Associate Professor, PhD, Docent
https://umbertopicchini.github.io/  , twitter: @uPicchini

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