Bayesian Regression Analysis using Median Rank Set Sampling

Authors

  • Inad Nawajah Department of Mathematics, College of Science and Technology, Hebron University
  • Hassan Kanj College of Engineering and Technology, American University of the Middle East, Egaila 54200, Kuwait
  • Yehia Kotb College of Engineering and Technology, American University of the Middle East, Egaila 54200, Kuwait
  • Julian Hoxha College of Engineering and Technology, American University of the Middle East, Egaila 54200, Kuwait
  • Mouhammad Alakkoumi
  • Kamel Jebreen Palestine Technical University

DOI:

https://doi.org/10.29020/nybg.ejpam.v17i1.5015

Keywords:

Median Ranked Set Sampling, Bayes factor, Regression, Bayesian approach

Abstract

Bayesian estimation of the linear regression parameter system is considered by deploying Median Rank Set Sampling (MRSS). The full conditional distributions and the associated posterior distribution are obtained. Therefore, based on Markov Chain Monte Carlo simulation, the Bayesian point estimates and credible intervals for the regression parameters are determined. To measure the efficiency of the obtained Bayesian estimates concerning the frequentist estimates we compute the asymptotic relative efficiency of the obtained Bayesian estimates using Markov Chain Monte Carlo simulation.

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Published

2024-01-31

Issue

Vol. 17 No. 1: (January 2024)

Section

Nonlinear Analysis

License

Copyright (c) 2024 European Journal of Pure and Applied Mathematics

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How to Cite

Bayesian Regression Analysis using Median Rank Set Sampling. (2024). European Journal of Pure and Applied Mathematics, 17(1), 180-200. https://doi.org/10.29020/nybg.ejpam.v17i1.5015