Two-Stage Shrinkage Bayesian Estimators For The Shape Parameter of Pareto Distribution Dependent on Katti’s Regions - Marwa Hashem Abd Ali; Alaa Khlaif Jiheel; Zuhair Al-Hemyari (Iraqi Journal for Computer Science and Mathematics, 2022)
This study proposes a two-stage shrinkage Bayesian estimation of the shape parameter of Pareto distribution. Additional information from the past and considered presently in new estimation processes has been receiving 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 of ? can take the form of an initial estimate ?0 of ?. The expressions for bias, bias ratio, mean square error, expected sample size, and relative efficiency are derived based on the two regions of R1 and R2. Certain values of the constants are considered, and the R language is used for statistical programming. The numerical results and conclusion suggest that the proposed estimators have higher relative efficiency compared with the classical Bayesian estimator with respect to a guess value. The effective region of the estimator dependent on R2 is better than that of the estimator dependent dependent on R1.