A new statistical framework for overdispersed count data: Applications in public health, radiation dosimetry and finance

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F25%3A10258695" target="_blank" >RIV/61989100:27240/25:10258695 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27740/25:10258695

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S1687850725006995" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1687850725006995</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.jrras.2025.101987" target="_blank" >10.1016/j.jrras.2025.101987</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A new statistical framework for overdispersed count data: Applications in public health, radiation dosimetry and finance

Popis výsledku v původním jazyce

Over-dispersed count data, where the variance exceeds the mean, appear in many fields and call for models that allow extra variability. We propose the Poisson-Juchez (PJCHZ) distribution, obtained by compounding a Poisson distribution with the Juchez distribution, to provide a flexible yet tractable framework for such data. We derive closed-form expressions for the rth factorial, raw, and central moments, and study key properties, including the probability generating function, dispersion behavior, reliability measures, stress-strength characteristics, and the Lorenz curve. Parameters are estimated by maximum likelihood, and we examine the finite-sample performance of the estimators through simulation. We then apply the PJCHZ model to three datasets on vaccine adverse events, cytogenetic radiation lesions, and insurance claim counts. Across these examples, the PJCHZ offers improved fit and greater flexibility compared with several competing distributions. These results indicate that the PJCHZ is a practical choice for modeling over-dispersed counts in public health, radiation dosimetry, and insurance analytics.

Název v anglickém jazyce

A new statistical framework for overdispersed count data: Applications in public health, radiation dosimetry and finance

Popis výsledku anglicky

Over-dispersed count data, where the variance exceeds the mean, appear in many fields and call for models that allow extra variability. We propose the Poisson-Juchez (PJCHZ) distribution, obtained by compounding a Poisson distribution with the Juchez distribution, to provide a flexible yet tractable framework for such data. We derive closed-form expressions for the rth factorial, raw, and central moments, and study key properties, including the probability generating function, dispersion behavior, reliability measures, stress-strength characteristics, and the Lorenz curve. Parameters are estimated by maximum likelihood, and we examine the finite-sample performance of the estimators through simulation. We then apply the PJCHZ model to three datasets on vaccine adverse events, cytogenetic radiation lesions, and insurance claim counts. Across these examples, the PJCHZ offers improved fit and greater flexibility compared with several competing distributions. These results indicate that the PJCHZ is a practical choice for modeling over-dispersed counts in public health, radiation dosimetry, and insurance analytics.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

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OECD FORD obor

10103 - Statistics and probability

Projekt

—

Návaznosti

—

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of Radiation Research and Applied Sciences

ISSN

1687-8507

e-ISSN

1687-8507

Svazek periodika

18

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

21

Strana od-do

101987

Kód UT WoS článku

001592468300001

EID výsledku v databázi Scopus

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