Robust-M new two-parameter estimator for linear regression models: Simulations and applications

Authors

  • Taiwo J. Adejumo
    Department of Statistics, Ladoke Akintola University of Technology, Ogbomoso, Oyo State, Nigeria
  • Kayode Ayinde
    Department of Statistics, Federal University of Technology, Akure, Nigeria; Department of Mathematics and Statistics, Northwest Missouri State University, Maryville, Missouri, USA
  • Abayomi A. Akomolafe
    Department of Statistics, Federal University of Technology, Akure, Nigeria
  • Olusola S. Makinde
    Department of Statistics, Federal University of Technology, Akure, Nigeria
  • Adegoke S. Ajiboye
    Department of Statistics, Federal University of Technology, Akure, Nigeria

Keywords:

Ordinary least squares, Multicollinearity, Outliers, Estimators, Simulation study

Abstract

In the presence of multicollinearity and outliers, the ordinary least squares estimator remains inconsistent and unreliable. Several estimators have been proposed that can co-handle the problems of multicollinearity and outliers simultaneously. However, there is still a need to explore some other robust methods when the two anomalies appear in the linear regression model and recommend it to end users of statistics. Therefore, this study proposed Robust-M New Two Parameter (RNTP) and examined its performance over some already existing ones in the presence of multicollinearity and outliers in the x-direction. The theoretical expression under some conditions was established to showcase the new estimator's superiority. A simulation study was carried out alongside some factors to show that the RNTP is better than all other estimators considered in the study. The simulation study results revealed that RNTP outperformed other estimators in the study using the minimum MSE as the criterion. Likewise, real-life data was applied to affirm this claim.

Dimensions

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Published

2023-11-11

How to Cite

Robust-M new two-parameter estimator for linear regression models: Simulations and applications. (2023). African Scientific Reports, 2(3), 138. https://doi.org/10.46481/asr.2023.2.3.138

Issue

Volume 2, Issue 3, December 2023

Section

Original Research
Copyright & Licensing

Copyright (c) 2023 Taiwo J. Adejumo, Kayode Ayinde, Abayomi A. Akomolafe, Olusola S. Makinde, Adegoke S. Ajiboye

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Robust-M new two-parameter estimator for linear regression models: Simulations and applications. (2023). African Scientific Reports, 2(3), 138. https://doi.org/10.46481/asr.2023.2.3.138

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