EconPapers    
Economics at your fingertips  
 

Doubly bounded exponential model: Some information measures and estimation

Brijesh P. Singh, Utpal Dhar Das, Kadir Karakaya, Hassan S. Bakouch and Badamasi Abba

Communications in Statistics - Theory and Methods, 2024, vol. 53, issue 22, 7842-7859

Abstract: A three-parameter probability distribution is derived from a composed cumulative distribution function, which is itself a family of bounded support transformations. The transformed model called the doubly bounded exponential distribution, which exhibits decreasing shaped density while the hazard rate has increasing shape. Some statistical properties are obtained in closed form, such as the moments and various entropy functions. The parameter estimation is carried out by the methods of maximum likelihood estimate, least squares estimate, weighted least squares estimate, Anderson-Darling estimate, and Cramér-von Mises estimate. The performance of these estimators is assessed through a Monte Carlo simulation study. The identifiability of the DB-Exp model’s parameters is also investigated. The proposed distribution can produce a higher performance than several well-known bounded distributions in the literature, as shown by an application to rainfall data.

Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2023.2273779 (text/html)
Access to full text is restricted to subscribers.

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:taf:lstaxx:v:53:y:2024:i:22:p:7842-7859

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2023.2273779

Access Statistics for this article

Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe

More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:lstaxx:v:53:y:2024:i:22:p:7842-7859