scholarly journals Inference Based on Type-II Hybrid Censored Data from a Pareto Distribution

2020 ◽  
Author(s):  
Çağatay Çetinkaya
Keyword(s):  
Censored Data ◽  
Pareto Distribution ◽  
Bayes Estimation ◽  
Estimation Methods ◽  
Type Ii ◽  
Simulation Studies ◽  
Shape Parameters ◽  
Hybrid Censoring ◽  
Approximate Confidence Intervals ◽  
Censoring Scheme

The Pareto distribution takes part in life-testing experiments as a finite range distribution. In this study, inference studies for the scale and shape parameters of the Pareto distribution under type-II hybrid censoring scheme are considered. The main reason for choosing this censoring scheme is its advantage of guaranteeing at least particular failures to be observed by the end of the experiment. Maximum likelihood and Bayes estimation methods are used with their approximate confidence intervals. Proposed estimation methods are compared numerically based on simulation studies. A numerical example is also used to illustrate the theoretical outcomes.

Inferences for New Weibull-Pareto Distribution Based on Progressively Type-II Censored Data

2016 ◽  
Vol 5 (3) ◽  
pp. 501-514 ◽  
Author(s):  
Mohamed A. W. Mahmoud ◽  
Rashad M. EL-Sagheer ◽  
Samah H. M. Abdallah
Keyword(s):  
Censored Data ◽  
Pareto Distribution ◽  
Type Ii ◽  
Type Ii Censored Data

scholarly journals Bayesian inference for Rayleigh Pareto distribution under progressively type-II right censored data

2021 ◽  
pp. 729-743
Author(s):  
Assia Chadli ◽  
Sara Kermoune
Keyword(s):  
Censored Data ◽  
Pareto Distribution ◽  
Type Ii ◽  
Bayes Estimators ◽  
Right Censored Data ◽  
Inference Problems ◽  
Reliability Characteristics ◽  
Distribution Parameters ◽  
Likelihood Approach ◽  
Pitman Closeness

In this paper, we consider inference problems including estimation for a Rayleigh Pareto (RP) distribution under progressively type-II right censored data. We use two approaches, the classical maximum likelihood approach and the Bayesian approach for estimating the distribution parameters and the reliability characteristics. Bayes estimators and corresponding posterior risks (PR) have been derived using different loss functions (symmetric and asymmetric). The estimators cannot be obtained explicitly, so we use the method of Monte Carlo. Finally, we use the integrated mean square error (IMSE) and the Pitman closeness criterion to compare the results of the two methods.

scholarly journals Estimation procedures on Type-II censored data from a scaled Muth distribution

2021 ◽  
pp. 148-158
Author(s):  
Hayrinisa Demirci BIÇER
Keyword(s):  
Censored Data ◽  
Mean Squared Error ◽  
Real Life ◽  
Model Parameters ◽  
Type Ii ◽  
Monte Carlo Simulation Study ◽  
Anal Ysis ◽  
Squared Error ◽  
Type Ii Censored Data ◽  
Censoring Scheme

In the present paper, we consider the estimation problem for the scaled Muth distribution under Type-II censoring scheme. In order to estimate the model parameters α and β, the maximum likelihood, the least-squares, and the maximum spacing estimators are derived. To show estimation efficiencies of the estimators obtained with this paper, we present an exten- sive Monte-Carlo simulation study in which the estimators are compared according to bias and mean squared error criteria. Furthermore, we evaluate the applicability of the scaled Muth distribution by taking into account both full and Type-II censored data situations by an anal- ysis conducted on a real-life dataset.

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