Zero-modified Poisson-Modification of Quasi Lindley distribution and its application

Tharshan Ramajeyam () and Wijekoon Pushpakanthie ()
Additional contact information
Tharshan Ramajeyam: Postgraduate Institute of Science, University of Peradeniya, Peradeniya, Sri Lanka & Department of Mathematics and Statistics, University of Jaffna, Jaffna, Sri Lanka .
Wijekoon Pushpakanthie: Department of Statistics and Computer Science, University of Peradeniya, Peradeniya, Sri Lanka .

Statistics in Transition New Series, 2022, vol. 23, issue 4, 113-128

Abstract: The Poisson-Modification of Quasi Lindley (PMQL) distribution is a newly introduced mixed Poisson distribution for over-dispersed count data. The aim of this article is to introduce the Zero-modified PMQL (ZMPMQL) distribution as an alternative to the PMQL distribution in order to accommodate zero inflation/deflation. The method of obtaining the ZMPMQL distribution jointly with some of its important properties, namely the probability mass and distribution functions, mean, variance, index of dispersion, and quantile function are presented. Furthermore, some of its special cases are discussed. The maximum likelihood (ML) estimation method is used for the unknown parameter estimation. A simulation study is conducted in order to evaluate the asymptotic theory of the ML estimation method and to show the superiority of the ML method over the method of moments estimation. The applicability of the introduced distribution is illustrated by using a real-world data set.

Keywords: over-dispersion; mixed Poisson distribution; PMQL distribution; zero modification; maximum likelihood estimation (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.2478/stattrans-2022-0045 (text/html)

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:vrs:stintr:v:23:y:2022:i:4:p:113-128:n:9

DOI: 10.2478/stattrans-2022-0045

Access Statistics for this article

Statistics in Transition New Series is currently edited by Włodzimierz Okrasa

More articles in Statistics in Transition New Series from Statistics Poland
Bibliographic data for series maintained by Peter Golla ().