Classical and Bayesian estimation for Gompertz distribution under the unified hybrid censored sampling with application
Source abstract
Abstract
This study discusses the Gompertz distribution’s statistical inference using unified hybrid censored data. Under various loss functions, the maximum likelihood and Bayesian approaches are explored for estimating the parameters for the Gompertz distribution. To compare the suggested methodologies, the Monte Carlo simulation is used, which also introduces the simulation research. By examining a genuine dataset, the applicability of the presented inference in practice is finally demonstrated.
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Research context
OpenAlex topics: Statistical Distribution Estimation and Applications · Probabilistic and Robust Engineering Design · Statistical Methods and Bayesian Inference
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Statistics, Faculty of Commerce, Zagazig University 1 , Zagazig 44519, Egypt
Department of Mathematical Sciences, College of Science, Princess Nourah bint Abdulrahman University 2 , P.O. Box 84428, Riyadh 11671, Saudi Arabia
3 Mathematics Department, Faculty of Sciences, Umm Al-Qura University, Makkah, Saudi Arabia
Funding
Deanship of Scientific Research, Princess Nourah Bint Abdulrahman University
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