scholarly journals Bayesian Analysis for Lognormal Distribution under Progressive Type-II Censoring

2018 ◽  
Vol 48 (4) ◽  
Author(s):  
Sukhdev Singh ◽  
Yogesh Mani Tripathi ◽  
Shuo-Jye Wu
Keyword(s):  
Bayesian Analysis ◽  
Lognormal Distribution ◽  
Type Ii ◽  
Type Ii Censoring ◽  
Progressive Type ◽  
Progressive Type Ii Censoring

On estimation ofR=P(Y

2012 ◽  
Vol 82 (5) ◽  
pp. 729-744 ◽  
Author(s):  
Buğra Saraçoğlu ◽  
Ismail Kinaci ◽  
Debasis Kundu
Keyword(s):  
Exponential Distribution ◽  
Type Ii ◽  
Type Ii Censoring ◽  
Progressive Type ◽  
Progressive Type Ii Censoring

Estimation for flexible Weibull extension under progressive Type-II censoring

2021 ◽  
Vol 13 (1) ◽  
pp. 21-42
Author(s):  
Sanjay Kumar Singh ◽  
Umesh Singh ◽  
Vikas Kumar Sharma ◽  
Manoj Kumar
Keyword(s):  
Type Ii ◽  
Type Ii Censoring ◽  
Progressive Type ◽  
Progressive Type Ii Censoring

scholarly journals Estimations of Weibull-Geometric Distribution under Progressive Type II Censoring Samples

2015 ◽  
Vol 05 (07) ◽  
pp. 721-729 ◽  
Author(s):  
Azhari A. Elhag ◽  
Omar I. O. Ibrahim ◽  
Mohamed A. El-Sayed ◽  
Gamal A. Abd-Elmougod
Keyword(s):  
Geometric Distribution ◽  
Type Ii ◽  
Type Ii Censoring ◽  
Progressive Type ◽  
Progressive Type Ii Censoring

scholarly journals Different Approaches to Estimation of the Gompertz Distribution under the Progressive Type-II Censoring Scheme

2020 ◽  
Vol 2020 ◽  
pp. 1-7
Author(s):  
Kyeongjun Lee ◽  
Jung-In Seo
Keyword(s):  
Nuisance Parameter ◽  
Estimation Method ◽  
Real Data ◽  
Type Ii ◽  
Gompertz Distribution ◽  
Type Ii Censoring ◽  
Scale Parameters ◽  
Progressive Type ◽  
Censoring Scheme ◽  
Progressive Type Ii Censoring

This paper provides an estimation method for an unknown parameter by extending weighted least-squared and pivot-based methods to the Gompertz distribution with the shape and scale parameters under the progressive Type-II censoring scheme, which induces a consistent estimator and an unbiased estimator of the scale parameter. In addition, a way to deal with a nuisance parameter is provided in the pivot-based approach. For evaluation and comparison, the Monte Carlo simulations are conducted, and real data are analyzed.

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