The Fréchet Topp Leone-G Family of Distributions: Properties, Characterizations and Applications

Hesham Reyad (), Mustafa Ç. Korkmaz (), Ahmed Z. Afify (), G. G. Hamedani () and Soha Othman ()
Additional contact information
Hesham Reyad: Qassim University
Mustafa Ç. Korkmaz: Artvin Çoruh University
Ahmed Z. Afify: Benha University
G. G. Hamedani: Marquette University
Soha Othman: Cairo University

Annals of Data Science, 2021, vol. 8, issue 2, No 9, 345-366

Abstract: Abstract A new family of continuous distributions which ensure model flexiblity, is introduced based on the Fréchet distribution and Topp Leone-G family. Two special sub-models of the new family are discussed. We provide some distributional properties of this family in the general setting such as the series expansions of density, moments, generating function, stress strength model, Rényi and Shannon entropies, probability weighted moments and order statistics. Certain characterizations of the proposed family are presented. The maximum likelihood estimates and the observed information matrix are obtained for the model parameters. We assess the performance of the maximum likelihood estimators by means of a graphical simulation study. The potentiality of the new class is shown via two applications to real data sets.

Keywords: Maximum likelihood; Order statistics; Stress strength model; Topp Leone-G family; T-X family; Characterizations (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://link.springer.com/10.1007/s40745-019-00212-9 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:8:y:2021:i:2:d:10.1007_s40745-019-00212-9

Ordering information: This journal article can be ordered from
https://www.springer ... gement/journal/40745

DOI: 10.1007/s40745-019-00212-9

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 ().