Modified MEWMA Control Scheme for an Analytical Process Data

Modified MEWMA Control Scheme for an Analytical Process Data

Alpaben K. Patel

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Jyoti Divecha

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University of Rajshahi

Modified MEWMA Control Scheme for an Analytical Process Data

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Abstract

This article introduces Multivariate Modified Exponentially Weighted Moving Average (MMOEWMA) control chart, a chart for detecting shifts of all kinds in case of highly first order vector autoregressive VAR (1) process. This chart is based on modified MEWMA control chart statistic which is a correction of MEWMA chart statistic. The performance of MMOEWMA chart is illustrated along with MEWMA chart for a chemical process data. The average run length (ARL) properties of MMOEWMA scheme are derived using Markov Chain approach. Algorithm for the ARL computation and R-program of monitoring MMOEWMA control chart are provided.

References

12 Cites in Article

Reference Format

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R-Program for monitoring Modified Multivariate Exponentially Weighted Moving Average Control Chart.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

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Not applicable for this article.

How to Cite This Article

Alpaben K. Patel. 2013. \u201cModified MEWMA Control Scheme for an Analytical Process Data\u201d. Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 13 (GJCST Volume 13 Issue C3): .

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GJCST Volume 13 Issue C3
Pg. 23- 33

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

abrupt change average run length MEWMA multivariate modified EWMA vector autoregressive

Submission ReceivedDecember 13, 2012
Peer Review Double Blind
Handling Editor
Accepted January 4, 2013
Published January 15, 2013

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v1.2

Issue date

April 5, 2013

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Article Matrices

Total Score: 102

Country: India

Subject: Global Journal of Computer Science and Technology - C: Software & Data Engineering

Authors: Alpaben K. Patel, Jyoti Divecha (PhD/Dr. count: 0)

View Count (all-time): 282

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Publish Date: 2013 04, Fri

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Total Views: 9707

Total Downloads: 2621

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