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- W4385766235 abstract "Abstract In statistical inference, the experimental results are usually considered precise information. However, these results cannot always be recorded or measured precisely, which is called Fuzzy data, which can be considered an imprecise type of data with a source of uncertainty. This paper presents a Fuzzy Bayesian estimation for Burr type-XII distribution parameters based on progressive type-II fuzzy order statistics. The Bayesian estimators have been derived by Tierney-Kadane and Monte Carlo integration approximations and compared with the exact Bayesian estimators, via Monte Carlo simulations. The simulation results indicated that the exact Bayes results provide better estimators and outperform the other approximation methods. Finally, a numerical example is given to demonstrate the efficiency of the proposed methods." @default.
- W4385766235 created "2023-08-12" @default.
- W4385766235 creator A5063081627 @default.
- W4385766235 date "2023-08-11" @default.
- W4385766235 modified "2023-09-28" @default.
- W4385766235 title "Bayesian Inference on the Burr type-XII Model Parameters Based on Progressive type-II Fuzzy Order Statistics" @default.
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- W4385766235 doi "https://doi.org/10.21203/rs.3.rs-3243454/v1" @default.
- W4385766235 hasPublicationYear "2023" @default.
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