One World ABC Seminar: Gael Martin

on the May 21, 2020

at 11:30 am [UK time]
For this fourth session of the One World ABC Seminar, Gael Martin from Monash University will talk about "Focused Bayesian Prediction"

Inspired by the "One World Probability Seminar", we decided to run The One World ABC Seminar, a weekly/fortnightly series of seminars that will take place on Blackboard Collaborate on Thursdays at 11.30am [UK time]. The idea is to gather members and disseminate results and innovation during these weeks and months under lockdown.


Gael Martin

Abstract
We propose a new method for conducting Bayesian prediction that delivers accurate predictions without correctly specifying the unknown true data generating process. A prior is de?ned over a class of plausible predictive models. After observing data, we update the prior to a posterior over these models, via a criterion that captures a user-speci?ed measure of predictive accuracy. Under regularity, this update yields posterior concentration onto the element of the predictive class that maximizes the expectation of the accuracy measure. In a series of simulation experiments and empirical examples we ?nd notable gains in predictive accuracy relative to conventional likelihood-based prediction.
References

[1] R. Loaiza-Maya, G. M. Martin, D. T. Frazier (2019). Focused Bayesian Prediction. arXiv:1912.12571.

 

 

Published on May 19, 2020