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Activity Number: 269 - Statistical Process Monitoring Methods
Type: Topic Contributed
Date/Time: Tuesday, August 9, 2022 : 10:30 AM to 12:20 PM
Sponsor: Quality and Productivity Section
Abstract #322353
Title: Multivariate Monitoring via Trees
Author(s): Eric Chicken* and Daniel Timme and Andres F. Barrientos and Debajyoti Sinha
Companies: Florida State University and Florida State University and Florida State University and Florida State University
Keywords: Statistical Process Control; CART; Random Trees; Nonparametric
Abstract:

We consider change-point detection and estimation in sequences of multivariate functional observations. A nonparametric method utilizing Classification and Regression Trees (CART) to build a sequence of regression trees is proposed which makes use of the Kolmogorov-Smirnov statistic to monitor profile behavior. Our novel method compares favorably to existing methods in the literature


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