Performance of a Class of Bayes Shrinkage Estimators Based on Rayleigh Record Data under Reflected Gamma Loss Function
This article addresses the problem of Bayesian shrinkage estimation for the Rayleigh scale parameter based on record values under the reflected gamma loss (RGL) function. A class of Bayesian shrinkage estimators using prior point information is constructed. The risk functions of the maximum likelihood estimator (MLE) and proposed Bayesian shrinkage estimator are derived under the RGL function. The performance of Bayesian shrinkage estimator is compared with the MLE numerically and graphically. One data set has been analyzed to illustrate the performance of the Bayesian shrinkage estimator.
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Optimal Repetitive Acceptance Sampling Inspection Plans by Attributes Based on Type I Censoring Using Two-point and Limited Weighted Methods
*, Zohre Mahdizadeh
Journal of Statistical Sciences, Spring-Summer 2025 -
Optimal double acceptance sampling inspection plans based on inverted Nadarajah-Haghighi distribution
*, Zohre Mahdizadeh
Journal of Decisions and Operations Research,