The Alpha Power Marshall-Olkin-G Distribution: Properties, and Applications
Joseph Thomas Eghwerido (),
Pelumi E. Oguntunde () and
Friday Ikechukwu Agu ()
Additional contact information
Joseph Thomas Eghwerido: Federal University of Petroleum Resources Effurun
Pelumi E. Oguntunde: Covenant University
Friday Ikechukwu Agu: University of Calabar
Sankhya A: The Indian Journal of Statistics, 2023, vol. 85, issue 1, No 6, 172-197
Abstract:
Abstract In this article, a new family of distribution called the alpha power Marshall-Olkin-G (APMO-G) family of distributions was proposed. The new family of distribution provides a better fit for continuous distributions for lifetime processes. The proposed family of distributions extends the existing alpha power transformed family of distributions by an additional parameter. A comprehensive reliability structural properties were derived. The moments, order statistics, hazard rate, and quantile functions, were also examined. The parameters of the proposed APMO-G model were obtained by the maximum likelihood method. Monte Carlo simulation was used to access the performance of the estimators. The goodness-of-fit test statistics were examined by means of two real-life data sets to demonstrate empirical flexibility. The results show that the APMO-G density provides a better fit when compared with other existing models and can serve as a better alternative model in the literature.
Keywords: Alpha power distribution; Burr-XII distribution; Bayesian inference; Gompertz distribution; Marshall-Olkin distribution; Moment generating function.; Primary 62E10; Secondary 62E15 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
http://link.springer.com/10.1007/s13171-020-00235-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:spr:sankha:v:85:y:2023:i:1:d:10.1007_s13171-020-00235-y
Ordering information: This journal article can be ordered from
http://www.springer.com/statistics/journal/13171
DOI: 10.1007/s13171-020-00235-y
Access Statistics for this article
Sankhya A: The Indian Journal of Statistics is currently edited by Dipak Dey
More articles in Sankhya A: The Indian Journal of Statistics from Springer, Indian Statistical Institute
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().