Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/236800 
Year of Publication: 
2020
Citation: 
[Journal:] Statistics in Transition New Series [ISSN:] 2450-0291 [Volume:] 21 [Issue:] 3 [Publisher:] Exeley [Place:] New York [Year:] 2020 [Pages:] 171-184
Publisher: 
Exeley, New York
Abstract: 
A new over-dispersed discrete probability model is introduced, by compounding the Poisson distribution with the weighted Ishita distribution. The statistical properties of the newly introduced distribution have been derived and discussed. Parameter estimation has been done with the application of the maximum likelihood method of estimation, followed by the Monte Carlo simulation procedure to examine the suitability of the ML estimators. In order to verify the applicability of the proposed distribution, a real-life set of data from the medical field has been analysed for modeling a count dataset representing epileptic seizure counts.
Subjects: 
compounding model
coverage probability
simulation
count data
epileptic seizure counts
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by-nc-nd Logo
Document Type: 
Article

Files in This Item:
File
Size





Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.