The Beta Exponential Power Series Distribution
Nafiseh Khojastehbakht (),
Amirhossein Ghatari () and
Ehsan Bahrami Samani ()
Additional contact information
Nafiseh Khojastehbakht: Shahid Beheshti University
Amirhossein Ghatari: Amirkabir University of Technolgy
Ehsan Bahrami Samani: Shahid Beheshti University
Annals of Data Science, 2023, vol. 10, issue 5, No 1, 1157-1178
Abstract:
Abstract In this paper, we investigate to propose a new statistical distribution based on power series. We introduce a new family of distributions which are constructed based on a latent complementary risk problem and are obtained by compounding Beta Exponential (BE) and Power Series distributions. The new distribution contains, as special sub-models, several important distributions which are discussed in the literature, such as Beta Exponential Poisson (BEP) distribution, Beta Exponential Geometric (BEG) distribution, Beta Exponential Logarithmic (BEL) distribution, Beta Exponential Binomial (BEB) distribution as special cases. The hazard function of the BEPS distributions can be increasing, decreasing or bathtub shaped among others. The comprehensive mathematical properties of the new distribution is provided such as closed-form expressions for the density, cumulative distribution, survival function, failure rate function, the r-th raw moment, maximum likelihood estimation and also the moments of order statistics. The proposed type of distributions is used to modeling simulated and real datasets.
Keywords: Beta exponential; Power series distributions; Hazard function; Maximum likelihood estimation (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/s40745-022-00414-8 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:aodasc:v:10:y:2023:i:5:d:10.1007_s40745-022-00414-8
Ordering information: This journal article can be ordered from
https://www.springer ... gement/journal/40745
DOI: 10.1007/s40745-022-00414-8
Access Statistics for this article
Annals of Data Science is currently edited by Yong Shi
More articles in Annals of Data Science from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().