JSM 2004 - Toronto

Abstract #302203

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Activity Number: 429
Type: Contributed
Date/Time: Thursday, August 12, 2004 : 10:30 AM to 12:20 PM
Sponsor: Section on Quality and Productivity
Abstract - #302203
Title: On Detection of Changes in Count Data
Author(s): Emmanuel Yashchin*+
Companies: IBM Research
Address: IBM, T.J. Watson Research Ctr., Box 218, Yorktown Heights, NY, 10598,
Keywords: categorical data ; control schemes ; cusum ; sequential analysis
Abstract:

The problem of monitoring count data is encountered in a wide range of practical settings. For example, in the field of manufacturing, problems of this type include monitoring defect rates, levels of contamination or data integrity. This paper discusses an approach to monitoring in situations where the underlying parameters of the model are subject to abrupt changes of unpredictable magnitude at some unknown points in time. We derive detection schemes based on the likelihood-ratio approach and discuss their performance and issues related to their design and analysis. The paper also discusses problems related to online estimation of the parameters in the presence of abrupt changes. It contains several examples that illustrate use of the proposed techniques in semiconductor industry.

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