Hameedah  Naeem Melik, Nor  Aishah Ahad, Sharipah  Soaad Syed Yahaya, 
    Modified One-Step M-Estimator with Robust Scale Estimator for
Multivariate Data,
    Journal of Engineering and Applied Sciences,
    Volume 13,Issue 24,
    2018,
    Pages 10396-10400,
    ISSN 1816-949x,
    jeasci.2018.10396.10400,
    (https://makhillpublications.co/view-article.php?doi=jeasci.2018.10396.10400)
    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<sub>n</sub>, in the trimming criterion of MOM. This introduces a new robust approach termed RLDA<sub>MQ</sub> for handling outliers encountered in multivariate data. The results show the superiority of RLDA<sub>MQ</sub> over the classical LDA and previously existing robust method in literature in terms of misclassification error evaluated through simulated data.
    Keywords: robust;Q;Modified one-step M-estimator;encountered;trimming criterion;multivariate data