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Activity Number:
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268
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Type:
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Topic Contributed
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Date/Time:
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Tuesday, August 8, 2006 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Quality and Productivity
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| Abstract - #307140 |
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Title:
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A Bayesian Approach in Modeling Shifts of the Mean/Variance of Count Data
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Author(s):
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Panagiotis Tsiamyrtzis*+ and Douglas M. Hawkins
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Companies:
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Athens University of Economics and Business and University of Minnesota
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Address:
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76 Patission Street, Athens, 10434, Greece
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Keywords:
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Bayesian SPC by attributes ; change point ; gamma mixture
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Abstract:
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We consider a process producing count data from a Poisson distribution. Our interest is in detecting online whether the Poisson parameter (mean and variance) shifts to either a higher value (causing worst process performance) or a smaller value (good scenario). The necessity for drawing inference sequentially as the observations become available leads us to adopt a Bayesian sequentially updated scheme of mixture of gamma distributions. Issues regarding inference and prediction will be covered. The developed methodology is appealing in cases of short runs and/or Phase I count data.
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