Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/266288 
Year of Publication: 
2021
Citation: 
[Journal:] Statistics in Transition New Series [ISSN:] 2450-0291 [Volume:] 22 [Issue:] 4 [Publisher:] Exeley [Place:] New York [Year:] 2021 [Pages:] 171-189
Publisher: 
Exeley, New York
Abstract: 
The exponentiated Burr Type XII (EBXII) distribution has wide applications in reliability and economic studies. In this article, the estimation of the probability density function and the cumulative distribution function of EBXII distribution is considered. We examine the maximum likelihood estimator, the uniformly minimum variance unbiased estimator, the least squares estimator, the weighted least squares estimator, the maximum product spacing estimator, the Cramér-von-Mises estimator, and the Anderson-Darling estimator. We derive analytical forms for the bias and mean square error. A simulation study is performed to investigate the consistency of the suggested methods of estimation. Data relating to the wind speed and service times of aircraft windshields are used with the studied methods. The simulation studies and real data applications have revealed that the maximum likelihood estimator performs more efficiently than its remaining counterparts.
Subjects: 
exponentiated Burr Type XII model
least squares estimator
maximum likelihood estimator
uniform minimum variance unbiased estimator
weighted least squares estimator
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

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