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

• Authors: Bilal Ahmad Para , Tariq Rashid Jan

Abstracts

EN

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.

Keywords

EN

compounding model; coverage probability; simulation; count data; epileptic seizure counts

• Publisher: Główny Urząd Statystyczny
• Journal: Statistics in Transition new series
• Year: 2020
• Volume: 21
• Issue: 3
• Pages: 171-184

Contributors

author

Bilal Ahmad Para

• Department of Statistics, GDC Anantnag, J&K, India

• https://orcid.org/0000000200773391

author

Tariq Rashid Jan

• Department of Statistics, University of Kashmir, India

• https://orcid.org/0000000200930748

Identifiers

DOI

10.21307/stattrans-2020-050

Biblioteka Nauki

1058917