Nonparametric Robust Estimator for Slop Parameter in Linear Structural Relationship Model

Date

2022-1

Type

Article

Journal title

ZULFAQAR International Journal of Defence Science, Engineering & Technology

Issue

Vol. 2018 No. 2

Author(s)

Amel Saad Alshargawi

Pages

1 - 8

Abstract

In this study, the linear structural relationship model’s slope parameter is determined by using the proposed robust nonparametric method based on trimmed mean. This method is an upgrade to the nonparametric method that was put forward by Al-Nasser and Ebrahem (2005) by employing trimmed mean for all likely paired slopes rather than median slopes. Simulation study and real data were used to compare the proposed method’s performance versus the traditional maximum likelihood method. In the simulation study, based on both methods’ mean square error, it was inferred that the MLE method breaks down due to the presence of outliers even though its functioning was not affected when there was no outlier in the data set. Based on the real life example, it can be concluded that the performance of our proposed method was quite well in determining slope parameter

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