JSM 2005 - Toronto

Abstract #302779

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 377
Type: Invited
Date/Time: Wednesday, August 10, 2005 : 10:30 AM to 12:20 PM
Sponsor: SSC
Abstract - #302779
Title: A Likelihood-based Approach
Author(s): Jason Loeppky*+ and Derek Bingham and William J. Welch
Companies: University of British Columbia and Simon Fraser University and University of British Columbia
Address: Department of Statistics, Vancouver, BC, V6T 1Z2, Canada
Keywords:
Abstract:

In many forms of scientific investigation, mathematical computer models are used to analyze complex physical systems. It is often necessary to calibrate the computer model using some observed data on the process. In this talk, we will discuss some of the issues surrounding model calibration, particularly a maximum likelihood method to find estimates of the calibration parameters. We will show the MLE is not necessarily the value of the calibration parameters that minimizes the bias, rather the value that makes the bias function simple to model. The Likelihood approach will be demonstrated through a series of examples, and results will be compared to a full Bayesian analysis.

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