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Author
Abu Awwad Raed R. (University of Petra, Amman, Jordan), Bdair Omar M. (Al-Balqa Applied University, Amman, Jordan), Abufoudeh Ghassan K. (University of Petra, Amman, Jordan)
Title
Bayesian Estimation and Prediction Based on Rayleigh Record Data with Applications
Source
Statistics in Transition, 2021, vol. 22, nr 3, s. 59-79, tab., wykr., bibliogr. 24 poz.
Keyword
Estymacja bayesowska, Metoda Monte Carlo, Łańcuch Markowa
Bayesian estimation, Monte Carlo method, Markov chain
Note
summ.
Abstract
Based on a record sample from the Rayleigh model, we consider the problem of estimatingthe scale and location parameters of the model and predicting the future unobserved recorddata. Maximum likelihood and Bayesian approaches under different loss functions are usedto estimate the model's parameters. The Gibbs sampler and Metropolis-Hastings methodsare used within the Bayesian procedures to draw the Markov Chain Monte Carlo (MCMC)samples, used in turn to compute the Bayes estimator and the point predictors of the futurerecord data. Monte Carlo simulations are performed to study the behaviour and to comparemethods obtained in this way. Two examples of real data have been analyzed to illustrate theprocedures developed here.(original abstract)
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The Library of Warsaw School of Economics
The Library of University of Economics in Katowice
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Bibliography
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ISSN
1234-7655
Language
eng
URI / DOI
http://dx.doi.org/10.21307/stattrans-2021-027
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