Artikel

Poisson Weighted Ishita Distribution: Model for Analysis of Over-Dispersed Medical Count Data

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.

Language
Englisch

Bibliographic citation
Journal: Statistics in Transition New Series ; ISSN: 2450-0291 ; Volume: 21 ; Year: 2020 ; Issue: 3 ; Pages: 171-184 ; New York: Exeley

Subject
compounding model
coverage probability
simulation
count data
epileptic seizure counts

Event
Geistige Schöpfung
(who)
Para, Bilal Ahmad
Jan, Tariq Rashid
Event
Veröffentlichung
(who)
Exeley
(where)
New York
(when)
2020

DOI
doi:10.21307/stattrans-2020-050
Handle
Last update
10.03.2025, 11:43 AM CET

Data provider

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Object type

  • Artikel

Associated

  • Para, Bilal Ahmad
  • Jan, Tariq Rashid
  • Exeley

Time of origin

  • 2020

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