Estimation of parameters of the exponentiated pareto distribution using ranked set sampling
Joint Authors
Abu Zaid, Nasir Ibrahim Nasir Rashwan
Ibrahim, Maha Faruq Tawfiq
Source
Scientific Journal for Commerce and Finance
Issue
Vol. 42, Issue 2 (30 Jun. 2022), pp.130-148, 19 p.
Publisher
Tanta University Faculty of Commerce
Publication Date
2022-06-30
Country of Publication
Egypt
No. of Pages
19
Main Subjects
Topics
Abstract EN
In this article, the maximum likelihood estimation method is used to estimate the unknown parameters of the exponentiated pareto distribution based on ranked set sampling (RSS), median ranked set sampling (MRSS) and simple random sample (SRS).
comparison between estimators of these techniques is made through simulation study using some criteria: biases, mean square errors and the relative efficiency.
at the same sample size, the study concluded that the estimators based on RSS and MRSS are more efficient than those obtained by the SRS.
American Psychological Association (APA)
Abu Zaid, Nasir Ibrahim Nasir Rashwan& Ibrahim, Maha Faruq Tawfiq. 2022. Estimation of parameters of the exponentiated pareto distribution using ranked set sampling. Scientific Journal for Commerce and Finance،Vol. 42, no. 2, pp.130-148.
https://search.emarefa.net/detail/BIM-1391817
Modern Language Association (MLA)
Abu Zaid, Nasir Ibrahim Nasir Rashwan& Ibrahim, Maha Faruq Tawfiq. Estimation of parameters of the exponentiated pareto distribution using ranked set sampling. Scientific Journal for Commerce and Finance Vol. 42, no. 2 (Jun. 2022), pp.130-148.
https://search.emarefa.net/detail/BIM-1391817
American Medical Association (AMA)
Abu Zaid, Nasir Ibrahim Nasir Rashwan& Ibrahim, Maha Faruq Tawfiq. Estimation of parameters of the exponentiated pareto distribution using ranked set sampling. Scientific Journal for Commerce and Finance. 2022. Vol. 42, no. 2, pp.130-148.
https://search.emarefa.net/detail/BIM-1391817
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references: p. 146-148
Record ID
BIM-1391817