Estimation parameters for the Binomial q-distribution

Bouzida Imed, Masmoudi Afif and Zitouni Mouna

Communications in Statistics - Theory and Methods, 2020, vol. 50, issue 21, 5101-5113

Abstract: The parameters estimation and simulation studies of two classical discrete Binomial and Bernoulli q-distributions are described. For the parameters estimation problem, two major methods are used and presented. The iterative EM-Newton–Raphson method based on maximum likelihood and Bayes Theorem which is formulated to estimate the parameter p of the Bernoulli q-distribution. The moments method is used for the estimation of the probability of success denoted [p]q for the Binomial q-distribution. The effectiveness and feasibility of the proposed models are also demonstrated through simulation studies for different q parameters values and samples sizes.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2020.1725825 (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:50:y:2020:i:21:p:5101-5113

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

DOI: 10.1080/03610926.2020.1725825

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 ().