Interval Estimation for Burr Type-X Distribution under Type-I Hybrid Progressive Censoring Scheme

2020 ◽  
Vol 9 (1) ◽  
pp. 51-59
Keyword(s):  
Interval Estimation ◽  
Type I ◽  
Progressive Censoring ◽  
Censoring Scheme

scholarly journals EM Algorithm for Mixture Distributions Model with Type-I Hybrid Censoring Scheme

Mathematics ◽  
2021 ◽  
Vol 9 (19) ◽  
pp. 2483
Author(s):  
Tzong-Ru Tsai ◽  
Yuhlong Lio ◽  
Wei-Chen Ting
Keyword(s):  
Expectation Maximization ◽  
Interval Estimation ◽  
Likelihood Estimation ◽  
Estimation Procedure ◽  
Maximum Likelihood Estimates ◽  
Model Parameters ◽  
Mixture Distributions ◽  
Type I ◽  
Censored Samples ◽  
Censoring Scheme

An expectation–maximization (EM) likelihood estimation procedure is proposed to obtain the maximum likelihood estimates of the parameters in a mixture distributions model based on type-I hybrid censored samples when the mixture proportions are unknown. Three bootstrap methods are applied to construct the confidence intervals of the model parameters. Monte Carlo simulations are conducted to evaluate the performance of the proposed methods. Simulation results show that the proposed methods can perform well to obtain reliable point and interval estimation results. Three examples are used to illustrate the applications of the proposed methods.

scholarly journals Estimations of the parameters of generalised exponential distribution under progressive interval type-I censoring scheme with random removals

2017 ◽  
Vol 46 (2) ◽  
pp. 33-47 ◽  
Author(s):  
Arun Kaushik ◽  
Aakriti Pandey ◽  
Sandeep Kumar Maurya ◽  
Umesh Singh ◽  
Sanjay Kumar Singh
Keyword(s):  
Exponential Distribution ◽  
Interval Estimation ◽  
Type I ◽  
Estimation Of Parameters ◽  
Type I Censoring ◽  
Bayesian Procedures ◽  
Maximum Likelihood Expectation Maximization ◽  
Censored Sample ◽  
Interval Type ◽  
Censoring Scheme

The present article aims to point and interval estimation of the parameters of generalised exponential distribution (GED) under progressive interval type-I (PITI) censoring scheme with random removals. The considered censoring scheme is most useful in those cases where continuous examination is not possible. Maximum likelihood, expectation-maximization and Bayesian procedures have been developed for the estimation of parameters of the GED, based on a PITI censored sample. Real datasets have been considered to illustrate the applicability of the proposed work. Further, we have compared the performances of the proposed estimators under PITI censoring to that of the complete sample.

scholarly journals A Progressive Interval Type-I Censored Life Test Plan for Rayleigh Distribution

2019 ◽  
Vol 48 (3) ◽  
pp. 76-86
Author(s):  
Arun Kaushik
Keyword(s):  
Rayleigh Distribution ◽  
Interval Censoring ◽  
Maximum Likelihood Estimates ◽  
Type I ◽  
Test Plan ◽  
Type I Censoring ◽  
Progressive Type ◽  
Interval Type ◽  
Censoring Scheme ◽  
Two Parameter

In this paper, we have considered the problem of optimal inspection times for the progressive interval type-I censoring scheme where uncertainty in the process is governed by the two-parameter Rayleigh distribution. Here, we also introduced some optimality criterion and determined the optimum inspection times, accordingly. The effect of the number of inspections and choice of optimally spaced inspection times based on the asymptotic relative efficiencies of the maximum likelihood estimates of the parameters are also investigated. Further, we have discussed the optimal progressive type-I interval censoring plan when the inspection times and the expected proportions of total failures in the experiment are under control.

Inferences for multiple interval type-I censoring scheme

2021 ◽  
pp. 1-20
Author(s):  
Shubham Agnihotri ◽  
Sanjay Kumar Singh ◽  
Umesh Singh
Keyword(s):  
Type I ◽  
Type I Censoring ◽  
Interval Type ◽  
Censoring Scheme
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