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E-Bayesian and Hierarchical Bayesian Estimations for the Inverse Weibull Distribution

E-Bayesian and Hierarchical Bayesian Estimations for the Inverse Weibull Distribution In this paper new formulas for E-Bayesian and hierarchical Bayesian estimations of the parameter and reliability of the inverse Weibull distribution are obtained in closed forms. To illustrate the applicability of the obtained results, simulated and real data are used which illustrate that E-Bayesian estimate gives superior performance much better than hierarchical Bayesian for the estimate of the parameter of the inverse Weibull distribution. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annals of Data Science Springer Journals

E-Bayesian and Hierarchical Bayesian Estimations for the Inverse Weibull Distribution

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References (29)

Publisher
Springer Journals
Copyright
Copyright © The Author(s), under exclusive licence to Springer-Verlag GmbH, DE part of Springer Nature 2021
ISSN
2198-5804
eISSN
2198-5812
DOI
10.1007/s40745-020-00320-x
Publisher site
See Article on Publisher Site

Abstract

In this paper new formulas for E-Bayesian and hierarchical Bayesian estimations of the parameter and reliability of the inverse Weibull distribution are obtained in closed forms. To illustrate the applicability of the obtained results, simulated and real data are used which illustrate that E-Bayesian estimate gives superior performance much better than hierarchical Bayesian for the estimate of the parameter of the inverse Weibull distribution.

Journal

Annals of Data ScienceSpringer Journals

Published: Jun 1, 2023

Keywords: Inverse Weibull distribution; E-Bayesian estimation; Hierarchical Bayesian estimation; Reliability; Simulation

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