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Monitoring multivariate simple linear profiles using robust estimators

Author

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  • Moslem Kordestani
  • Farid Hassanvand
  • Yaser Samimi
  • Hamid Shahriari

Abstract

This article focuses on estimation of multivariate simple linear profiles. While outliers may hamper the expected performance of the ordinary regression estimators, this study resorts to robust estimators as the remedy of the estimation problem in presence of contaminated observations. More specifically, three robust estimators M, S and MM are employed. Extensive simulation runs show that in the absence of outliers or for small amount of contamination, the robust methods perform as well as the classical least square method, while for medium and large amounts of contamination the proposed estimators perform considerably better than classical method.

Suggested Citation

  • Moslem Kordestani & Farid Hassanvand & Yaser Samimi & Hamid Shahriari, 2020. "Monitoring multivariate simple linear profiles using robust estimators," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 49(12), pages 2964-2989, June.
    • Handle: RePEc:taf:lstaxx:v:49:y:2020:i:12:p:2964-2989
    DOI: 10.1080/03610926.2019.1584314
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