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

The result's identifiers

  • Result code in 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>

  • Alternative codes found

    RIV/61989100:27740/25:10258695

  • Result on the web

    <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>

Alternative languages

  • Result language

    angličtina

  • Original language name

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

  • Original language description

    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.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10103 - Statistics and probability

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2025

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Journal of Radiation Research and Applied Sciences

  • ISSN

    1687-8507

  • e-ISSN

    1687-8507

  • Volume of the periodical

    18

  • Issue of the periodical within the volume

    4

  • Country of publishing house

    NL - THE KINGDOM OF THE NETHERLANDS

  • Number of pages

    21

  • Pages from-to

    101987

  • UT code for WoS article

    001592468300001

  • EID of the result in the Scopus database