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IDS.190 Topics in Bayesian Modeling and Computation
Esther Williams in the Harold Holt Memorial Swimming Pool: Some Thoughts on Complexity
October 23, 2019 @ 4:00 pm - 5:00 pm
Daniel Simpson (University of Toronto)
E18-304
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IDS.190 – Topics in Bayesian Modeling and Computation
Speaker:
Daniel Simpson (University of Toronto)
Abstract:
As data becomes more complex and computational modelling
becomes more powerful, we rapidly find ourselves beyond the scope of
traditional statistical theory. As we venture beyond the traditional
thunderdome, we need to think about how to cope with this additional
complexity in our model building. In this talk, I will talk about a
few techniques that are useful when specifying prior distributions and
building Bayesian models for complex data.
Bio:
Daniel Simpson is an Assistant Professor at the University of Toronto’s Department of Statistical Sciences.
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**Taking IDS.190 satisfies the seminar requirement for students in MIT’s Interdisciplinary Doctoral Program in Statistics (IDPS), but formal registration is open to any graduate student who can register for MIT classes. For more information and an up-to-date schedule, please see https://stellar.mit.edu/S/course/IDS/fa19/IDS.190/
**Meetings are open to any interested researcher.
