scholarly journals A New Rayleigh Distribution: Properties and Estimation Based on Progressive Type-II Censored Data with an Application

2022 ◽  
Vol 130 (1) ◽  
pp. 379-396
Author(s):  
Ali Algarni ◽  
Abdullah M. Almarashi
Keyword(s):  
Censored Data ◽  
Rayleigh Distribution ◽  
Type Ii ◽  
Progressive Type ◽  
Type Ii Censored Data

scholarly journals Bayesian Estimation Based on Rayleigh Progressive Type II Censored Data with Binomial Removals

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Reza Azimi ◽  
Farhad Yaghmaei
Keyword(s):  
Censored Data ◽  
Failure Time ◽  
Simulation Method ◽  
Reliability Function ◽  
Rayleigh Distribution ◽  
Type Ii ◽  
Monte Carlo Simulation Method ◽  
Bayesian Procedures ◽  
Progressive Type ◽  
Type Ii Censored Data

This study considers the estimation problem for the parameter and reliability function of Rayleigh distribution under progressive type II censoring with random removals, where the number of units removed at each failure time has a binomial distribution. We use the maximum likelihood and Bayesian procedures to obtain the estimators of parameter and reliability function of Rayleigh distribution. We also construct the confidence intervals for the parameter of Rayleigh distribution. Monte Carlo simulation method is used to generate a progressive type II censored data with binomial removals from Rayleigh distribution, and then these data are used to compute the point and interval estimations of the parameter and compare both the methods used with different random schemes.

scholarly journals Bayes Shrinkage Estimation of the Parameter of Rayleigh Distribution for Progressive Type-II Censored Data

2015 ◽  
Vol 44 (4) ◽  
pp. 3-15 ◽  
Author(s):  
Sanku Dey ◽  
Tanujit Dey ◽  
Sudhansu S. Maiti
Keyword(s):  
Censored Data ◽  
Empirical Bayes ◽  
Risk Function ◽  
Rayleigh Distribution ◽  
Shrinkage Estimation ◽  
Type Ii ◽  
Bayes Estimate ◽  
Data Set ◽  
Progressive Type ◽  
Type Ii Censored Data

This paper derives Bayes shrinkage estimator of Rayleigh parameter and its associated risk based on conjugate prior under the assumption of general entropy loss function for progressive type-II censored data. Risk function of maximum likelihood estimate, Bayes estimate and Bayes shrinkage estimate have also been derived and compared. A procedure has been suggested to include a guess value in case of the Bayes shrinkage estimation. Risk function of empirical Bayes estimate and empirical Bayes shrinkage estimate have also been derived and compared. In conclusion, an illustrative example is presented to assess how the Rayleigh distribution fits a real data set.

scholarly journals Estimating the Parameters of the Exponential-Geometric distribution based on progressively type-II censored data

2018 ◽  
Vol 6 (1) ◽  
pp. 37
Author(s):  
Aisha Fayomi ◽  
Hamdah Al-Shammari
Keyword(s):  
Censored Data ◽  
Geometric Distribution ◽  
Asymptotic Variance ◽  
Parameters Estimation ◽  
Type Ii ◽  
Progressive Type ◽  
The Em Algorithm ◽  
Asymptotic Confidence Intervals ◽  
Distribution Parameters ◽  
Type Ii Censored Data

This paper deals with the problem of parameters estimation of the Exponential-Geometric (EG) distribution based on progressive type-II censored data. It turns out that the maximum likelihood estimators for the distribution parameters have no closed forms, therefore the EM algorithm are alternatively used. The asymptotic variance of the MLEs of the targeted parameters under progressive type-II censoring is computed along with the asymptotic confidence intervals. Finally, a simple numerical example is given to illustrate the obtained results.

Sign in / Sign up

Export Citation Format

Share Document