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Control Charts for Overdispersed Count Data: Exploring the Poisson Chris-Jerry Distribution in Agriculture and Medicine

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F25%3A10257561" target="_blank" >RIV/61989100:27740/25:10257561 - isvavai.cz</a>

  • Result on the web

    <a href="https://onlinelibrary.wiley.com/doi/10.1002/qre.3745?af=R" target="_blank" >https://onlinelibrary.wiley.com/doi/10.1002/qre.3745?af=R</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1002/qre.3745" target="_blank" >10.1002/qre.3745</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Control Charts for Overdispersed Count Data: Exploring the Poisson Chris-Jerry Distribution in Agriculture and Medicine

  • Original language description

    Statistical process control (SPC) is vital for overseeing processes and ensuring quality standards, with control charts being key tools in this process. As manufacturing systems and components become more complex, there is an increasing demand for control charts built on advanced statistical distributions. The Poisson-based count chart is commonly used to monitor nonconformities in production, but its use depends on the assumption that the mean and variance of the data are equal. In many cases, particularly in fields such as biology and medicine, overdispersion occurs, where the variance surpasses the mean. In such cases, the Poisson Chris-Jerry (PSNCJ) distribution offers a more suitable approach for modeling count data. This study explores the development and characteristics of the PSNCJ distribution and presents control charts specifically designed for datasets that conform to this model. Its effectiveness is evaluated through both simulations and real-world applications. Moreover, the PSNCJ count chart is applied to datasets from agriculture and biology, demonstrating its practical significance in these fields. The results validate the utility and accuracy of the proposed control charts.

  • 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

    O - Projekt operacniho programu

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

    Quality and Reliability Engineering International

  • ISSN

    0748-8017

  • e-ISSN

    1099-1638

  • Volume of the periodical

    41

  • Issue of the periodical within the volume

    5

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    23

  • Pages from-to

    1913-1935

  • UT code for WoS article

    001431327100001

  • EID of the result in the Scopus database

    2-s2.0-85218700272