This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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103
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Type:
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Invited
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Date/Time:
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Monday, August 2, 2010 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Physical and Engineering Sciences
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Abstract - #305945 |
Title:
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Computer Experiments with Both Qualitative and Quantitative Inputs
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Author(s):
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William Notz*+ and Gang Han and Thomas J. Santner
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Companies:
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The Ohio State University and Moffitt Cancer Center & Research Institute and The Ohio State University
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Address:
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1958 Neil Avenue, Columbus, OH, 43210-1247,
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Keywords:
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computer experiments ;
qualitative inputs ;
ANOVA-decomposition
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Abstract:
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Gaussian Stochastic Process models are a popular way to model output from computer experiments. Unfortunately, the correlation functions typically used in these models assume inputs are quantitative. We propose a method for handling both quantitative and qualitative inputs. First, we consider an ANOVA-type decomposition of the output (as a function of the inputs) into an overall mean trend, first order departures from this mean trend, and higher order departures. Second, to model these trends we use a Bayesian approach with a prior on the correlation parameters that assumes they are draws from some common distribution. We demonstrate that our method works very well when there is a common underlying shape to the response for each value of the qualitative variables. Our method is also shown to compare favorably with other methods that have been recently proposed.
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