Journal of Engineering and Applied Sciences

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Modified One-Step M-Estimator with Robust Scale Estimator for Multivariate Data

Nor Aishah Ahad, Hameedah Naeem Melik and Sharipah Soaad Syed Yahaya
Page: 10396-10400 | Received 21 Sep 2022, Published online: 21 Sep 2022

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Abstract

The Modified One-step M-estimator (MOM) is a highly efficient robust estimator for classifying multivariate data. Generally, robust estimators came into existence as a solution to the inability of classical Linear Discriminant Analysis (LDA) to perform optimally in the presence of outliers. Thus, to solve this shortcoming, the robust MOM estimator is integrated with a highly robust scale estimator, Q_n, in the trimming criterion of MOM. This introduces a new robust approach termed RLDA_MQ for handling outliers encountered in multivariate data. The results show the superiority of RLDA_MQ over the classical LDA and previously existing robust method in literature in terms of misclassification error evaluated through simulated data.

How to cite this article:

Nor Aishah Ahad, Hameedah Naeem Melik and Sharipah Soaad Syed Yahaya. Modified One-Step M-Estimator with Robust Scale Estimator for Multivariate Data.
DOI: https://doi.org/10.36478/jeasci.2018.10396.10400
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2018.10396.10400