|
|
 |
| |
|
|
|
Bayesian and E-Bayesian Estimation for Rayleigh Distribution Using Unified Progressive Hybrid Censored Samples |
|
|
|
PP: 63-75 |
|
|
|
doi:10.18576/jsapl/100105
|
|
|
|
Author(s) |
|
|
|
Magdy Nagy,
|
|
|
|
Abstract |
|
|
| It is believed that the E-Bayesian estimation method will be able to solve the problems caused by the process of choosing the values of hyper-parameters for prior distributions in Bayesian estimates, which has attracted the attention of many authors. In this paper, these approaches are used based on the latest method of censored sample called unified progressive hybrid censored sample from the Rayleigh distribution are discussed. The Bayesian and E-Bayesian estimators are produced using four different loss functions. E-Bayesian estimation also made use of three more hyper-parameter distributions. Finally, in order to assess the applicability of the suggested model and different estimating techniques, the proposed model has been applied to real data.
|
|
|
|
|
|
|
|
