Profile control charts based on nonparametric L-1 regression methods

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Classical statistical process control often relies on univariate characteristics. In many contemporary applications, however, the quality of products must be characterized by some functional relation between a response variable and its explanatory variables. Monitoring such functional profiles has been a rapidly growing field due to increasing demands. This paper develops a novel nonparametric L-1 location-scale model to screen the shapes of profiles. The model is built on three basic elements: location shifts, local shape distortions, and overall shape deviations, which are quantified by three individual metrics. The proposed approach is applied to the previously analyzed vertical density profile data, leading to some interesting insights.

Original languageEnglish (US)
Pages (from-to)409-427
Number of pages19
JournalAnnals of Applied Statistics
Volume4
Issue number1
DOIs
StatePublished - Mar 1 2010

Fingerprint

Control Charts
Regression
Statistical process control
Location-scale Model
Statistical Process Control
Density Profile
Univariate
Monitoring
Deviation
Vertical
Metric
Profile
Control charts
Regression method
Model

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Modeling and Simulation
  • Statistics, Probability and Uncertainty

Cite this

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Profile control charts based on nonparametric L-1 regression methods. / Wei, Ying; Zhao, Zhibiao; Lin, Dennis K.J.

In: Annals of Applied Statistics, Vol. 4, No. 1, 01.03.2010, p. 409-427.

Research output: Contribution to journalArticle

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