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Performance of the hotelling T2 control chart for compositional data in the presence of measurement errors

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  • F. S. Zaidi
  • P. Castagliola
  • K. P. Tran
  • M. B. C. Khoo

Abstract

In statistical process monitoring, the presence of measurement errors is known to impact the performance of control charts. This paper makes an attempt to investigate the performance of the Hotelling CoDa (Compositional Data) $T^2 $T2 control chart in the presence of measurement errors. A linearly covariate measurement error model for CoDa is introduced to study the influence of the measurement device parameters ( $\sigma _{{\rm M}} $σM and b) and the number of independent observations m on the performance of the Hotelling CoDa $T^2 $T2 control chart in the in- and out-of-control cases. A realistic illustrative example based on the production of muesli is used to illustrate the estimation of the measurement device parameters and the in-control process parameters, as well as to demonstrate the ability of this control chart to efficiently detect changes in the muesli composition.

Suggested Citation

  • F. S. Zaidi & P. Castagliola & K. P. Tran & M. B. C. Khoo, 2019. "Performance of the hotelling T2 control chart for compositional data in the presence of measurement errors," Journal of Applied Statistics, Taylor & Francis Journals, vol. 46(14), pages 2583-2602, October.
    • Handle: RePEc:taf:japsta:v:46:y:2019:i:14:p:2583-2602
    DOI: 10.1080/02664763.2019.1605339
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    Cited by:

    1. Song, Zhi & Mukherjee, Amitava & Zhang, Jiujun, 2021. "Some robust approaches based on copula for monitoring bivariate processes and component-wise assessment," European Journal of Operational Research, Elsevier, vol. 289(1), pages 177-196.

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