A Poisson Quasi Suja Distribution
Article Sidebar
Page Numbers:
193-200
Digital Object Identifier:
Viewed: 208 times
Downloaded: 181 times
LYAS Publisher cordially invites qualified professionals to serve as Editors or Reviewers. Your expertise will make an important contribution to maintaining and strengthening the academic quality of our publications. Interested applicants are kindly requested to complete the application form at the following link: Editors & Reviewers
Please feel free to contact us if you need any further information about the submission process or if you have any additional questions.
Authors:Adeniyi Oyewole Ogunmola1*, Olateju Alao Bamigbala2
Copyright :Authors retain copyright and grant the journal right of first publication.
Main Article Content
Abstract
Two-parameter Poisson Quasi Suja distribution (PQSD) derived from the two-parameter quasi suja distribution is proposed for extremely positively count data. Its survival and hazard functions, first four raw moments’ measures were expressed. The variance, coefficient of variation, index of dispersion, skewness and kurtosis were also obtained. The impacts of each parameter in the new distribution were assessed.
Citation Metrics:
Downloads
Citation Metrics & Similar Scopus Articles
-
Paul Shourov K. (2027)Critical review of tools and techniques for predicting microplastics pollution in watershed runoffEnvironmental Pollution and Management, 4, 27-47
-
Perezhogin V.Y. (2028)Image-Based FEM Modeling of the Stress State in Hypereutectic High-Chromium Cast IronsKompleksnoe Ispolzovanie Mineralnogo Syra, 346(3), 131-141
-
Berkinbayev G.D. (2028)Radioactivity as a prospecting indicator of rare earth, gold and polymetal deposits in eastern Kazakhstan and an indicator of increased radioecological hazard during their developmentKompleksnoe Ispolzovanie Mineralnogo Syra, 346(3), 40-51
Article Details
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
References
Aderoju S.A. (2020). A new generalized Poisson-Sujatha distribution and its applications, Applied Mathematical Sciences 14(5), 229-234. https://doi.org/10.12988/ams.2020.914185
Aderoju S. A., Adeniyi I., Olaifa J. B. and Olaosebikan A. (2023). On Poisson-Samade Distribution: Its Applications in Modelling Count Data. Earthline Journal of Mathematical Sciences. E-ISSN: 2581-8147 Volume 12, Number 2, Pages 255-270 https://doi.org/10.34198/ejms.12223.255270
Adetunji A.A. and Sabri S.R.M. (2023). An alternative count distribution for modeling dispersed observations, Pertanika J. Sci. & Technol. 31(3), 1587-1603. https://doi.org/10.47836/pjst.31.3.25
Aryuyuen S. (2022), The negative binomial-new generalized Lindley distribution for count data: Properties and application, Pakistan Journal of Statistics and Operation Research 18(1), 167-177. http://dx.doi.org/10.18187/pjsor.v18i1.2988
Jolayemi, E. T. and Aderoju S.A. (2023). “On Zero-Truncated Negative Binomial With Excess Ones”. Asian Journal of Probability and Statistics 22 (3):45-50. https://doi.org/10.9734/ajpas/2023/v22i3487.
Opone F.C, Izekor E.A., Akata I.U. and Osagiede F. E. U. (2021). A discrete analogue of the continuous Marshall-Olkin Weibull distribution with application to count data, Earthline Journal of Mathematical Sciences 5(2), 415-428. https://doi.org/10.34198/ejms.5221.415428
Shanker R., Upadhyay R., and Shukla K.K. (2022). A Quasi Suja Distribution. RT&A, No 3 (69) Volume 17.
Zhang X., Mallick H., Tang Z., Zhang L., Cui X., Benson A.K. and Yi N. (2017). Negative binomial mixed models for analyzing microbiome count data, BMC Bioinformatics 18, 4. https://doi.org/10.1186/s12859-016-1441-7