Abstract Details
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Activity Number:
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212
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Type:
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Invited
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Date/Time:
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Monday, August 5, 2013 : 2:00 PM to 3:50 PM
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Sponsor:
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Quality and Productivity Section
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| Abstract - #307077 |
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Title:
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Nonparametric Profile Monitoring
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Author(s):
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Peihua Qiu*+
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Companies:
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University of Minnesota
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Keywords:
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EWMA ;
Local Linear Kernel Smoothing ;
Mixed-Effects Models ;
Profile Monitoring ;
Statistical Process Control
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Abstract:
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Quality of a process is often characterized by the functional relationship between a response and one or more predictors. Profile monitoring is for checking the stability of this relationship over time. In the literature, some existing control charts are for monitoring parametric profiles, and they assume that within-profile observations are independent of each other, which is often invalid. Recently, there are a number of nonparametric profile monitoring schemes proposed. Some of them can accommodate the possible correlation among within-profile observations. In this talk, we discuss the pros and cons of different nonparametric profile monitoring schemes. We also introduce some recent developments on dynamic screening of irregular longitudinal patterns, which is closely related to the profile monitoring problem.
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Authors who are presenting talks have a * after their name.
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