ENBIS-8 in Athens

21 – 25 September 2008 Abstract submission: 14 March – 11 August 2008

A Bayesian Approach to Model Shifts in Poisson Data

24 September 2008, 09:40 – 10:00


Submitted by
Panagiotis Tsiamyrtzis
Panagiotis Tsiamyrtzis and Douglas M. Hawkins
Dept. of Statistics, Athens University of Economics and Business
We consider a process producing count data from a Poisson distribution. Our interest is in detecting on-line whether the Poisson parameter (mean and variance) shifts to either a higher value (causing worst process performance) or to smaller values (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 very appealing in cases like short runs and/or Phase I count data.

Bayesian SPC by attributes, Change Point, Gamma mixture.

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