Abstract
This study proposes a two-stage shrinkage Bayesian estimation of the shape parameter of Paretodistribution. Additional information from the past and considered presently in new estimation processes has beenreceiving considerable attention in the last few decades, especially when a sample unit is costly or difficult to obtain.The proposed two-stage pooling estimation procedure assumes that the prior knowledge ofθcan take the form ofan initial estimateθ0ofθ. The expressions for bias, bias ratio, mean square error, expected sample size, and relativeefficiency are derived based on the two regions ofR1andR2. Certain values of the constants are considered, andthe R language is used for statistical programming. The numerical results and conclusion suggest that the proposedestimators have higher relative efficiency compared with the classical Bayesian estimator with respect to a guessvalue. The effective region of the estimator dependent onR2is better than that of the estimator dependent dependentonR1.
Recommended Citation
Abd Ali, Marwa Hashem; Jiheel, Alaa Khlaif; and Hemyari, Zuhair Al
(2022)
"TWO-STAGE SHRINKAGE BAYESIAN ESTIMATORS FORTHE SHAPE PARAMETER OF PARETO DISTRIBUTIONDEPENDENT ON KATTI’S REGIONS,"
Iraqi Journal for Computer Science and Mathematics: Vol. 3:
Iss.
2, Article 5.
DOI: https://doi.org/10.52866/ijcsm.2022.02.01.005
Available at:
https://ijcsm.researchcommons.org/ijcsm/vol3/iss2/5
