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Autor
Para Bilal Ahmad (Department of Statistics, GDC Anantnag, J&K, India), Jan Tariq Rashid (Department of Statistics, University of Kashmir, India)
Tytuł
Poisson Weighted Ishita Distribution: Model for Analysis of Over-Dispersed Medical Count Data
Źródło
Statistics in Transition, 2020, vol. 21, nr 3, s. 171-184, rys., tab., bibliogr. s. 183-184
Słowa kluczowe
Rozkład Poissona, Rozkład prawdopodobieństwa, Model probabilistyczny
Poisson distribution, Probability distributions, Probabilistic model
Uwagi
summ.
Abstrakt
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. (original abstract)
Dostępne w
Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie
Biblioteka SGH im. Profesora Andrzeja Grodka
Biblioteka Główna Uniwersytetu Ekonomicznego w Katowicach
Pełny tekst
Pokaż
Bibliografia
Pokaż
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  13. SHANKER, R., SHUKLA, K. K., (2017). Ishita distribution and its Applications, Biometrics & Biostatistics International Journal, 5(2), pp. 1-9.
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  16. ZAMANI, H., ISMAIL, N., (2010). Negative Binomial-Lindley Distribution And Its Application. Journal of Mathematics and Statistics, 1, pp. 4-9.
Cytowane przez
Pokaż
ISSN
1234-7655
Język
eng
URI / DOI
http://dx.doi.org/10.21307/stattrans-2020-050
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