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Department Seminar Series: Matthew Plumlee, Assistant Professor, Industrial & Operations Engineering, University of Michigan

Bayesian calibration of inexact computational models using Gaussian processes
Friday, January 15, 2016
11:30 AM-12:30 PM
411 West Hall Map
Bayesian calibration is used to study computer models in the presence of both a calibration parameter and potential model bias. Using the predominant statistical methodology, the parameter's posterior can drastically change depending on the bias's prior. This effect can lead to unreasonable inference on the parameter. To date, there has been no generally accepted alternatives. This talk will discuss a promising solution whereby the prior on the bias function has an orthogonality property. The problems associated with Bayesian calibration are shown to be mitigated through analytic results and both numerical and real examples. This solution mechanism also impacts the design and analysis of computer experiments.
Building: West Hall
Website:
Event Type: Workshop / Seminar
Tags: seminar
Source: Happening @ Michigan from Department of Statistics, Department of Statistics Seminar Series