Multivariate process control chart based on sign and signed-rank tests for mixture distributions

Udom, Akaninyene Udo; Ugwu, Offorma S.; Ossai, Everetus O.; Udoh, Nse S.

doi:10.1080/09720510.2020.1826685

Cited by 1 publication

(1 citation statement)

References 8 publications

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“…Construction of control limits with a mixture of probability distribution applications in the multiple‐stream processes was proposed, and it presented an alternative solution to Shewhart charts in cases where there were different machines and product production flows (Vicentin et al, 2018). Nonparametric control charts including multivariate signed‐rank and multivariate sign control charts were applied on a mixture of multivariate normal and t‐distributions (Udom et al, 2021). In sensor networks and manufacturing technology, multivariate processes face a new challenge with high‐dimensional data.…”

Section: Control Chart Applicationmentioning

confidence: 99%

Tolerance limits for mixture‐of‐normal distributions with application to COVID‐19 data

Wang

2023

WIREs Computational Stats

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Tolerance intervals (TIs) are widely used in various applications including manufacturing engineers, clinical research, and pharmaceutical industries. TIs can be used to construct limits of control charts for monitoring quality characteristics. For manufacturing processes where multiple factors may contribute to defects or multiple‐stream processes, a mixture distribution of several suitable probabilistic models may be a better choice than a simple distribution for modeling the data. TIs for the normal mixture distribution have been studied in the literature. This article reviews the TIs of the normal mixture distribution, the applications of the mixture distribution, and the control charts of the mixture distribution. A rule for constructing modified two‐sided TIs of the normal mixture distribution is summarized, and this rule may be extended to construct modified two‐sided TIs for general mixture distributions. The feasibility of using TIs to build control charts for mixture distributions is also discussed. A real data example of coronavirus disease 2019 is used to illustrate the method by linking the TI to control charts.This article is categorized under: Statistical Learning and Exploratory Methods of the Data Sciences > Clustering and Classification

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Section: Control Chart Applicationmentioning

confidence: 99%

Tolerance limits for mixture‐of‐normal distributions with application to COVID‐19 data

Wang

2023

WIREs Computational Stats

View full text Add to dashboard Cite

show abstract

Multivariate process control chart based on sign and signed-rank tests for mixture distributions

Cited by 1 publication

References 8 publications

Tolerance limits for mixture‐of‐normal distributions with application to COVID‐19 data

Tolerance limits for mixture‐of‐normal distributions with application to COVID‐19 data

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