TY  - JOUR
T1  - Modified One-Step M-Estimator with Robust Scale Estimator for
Multivariate Data
AU - Naeem Melik, Hameedah AU - Aishah Ahad, Nor AU - Soaad Syed Yahaya, Sharipah 
JO  - Journal of Engineering and Applied Sciences
VL  - 13
IS  - 24
SP  - 10396
EP  - 10400
PY  - 2018
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2018.10396.10400
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2018.10396.10400
KW  - robust
KW  -Q
KW  -Modified one-step M-estimator
KW  -encountered
KW  -trimming criterion
KW  -multivariate data
AB  - 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.
ER  -