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A Novel Entropy-Transformed Inverse Weibull Distribution: Development, Properties, and Application in Diverse Data Modeling

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F25%3A10258405" target="_blank" >RIV/61989100:27240/25:10258405 - isvavai.cz</a>

  • Alternative codes found

    RIV/61989100:27740/25:10258405

  • Result on the web

    <a href="https://onlinelibrary.wiley.com/doi/10.1002/eng2.70171" target="_blank" >https://onlinelibrary.wiley.com/doi/10.1002/eng2.70171</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1002/eng2.70171" target="_blank" >10.1002/eng2.70171</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    A Novel Entropy-Transformed Inverse Weibull Distribution: Development, Properties, and Application in Diverse Data Modeling

  • Original language description

    Standard distributions must be improved to enhance their capacity for data modeling because they do not inherently suit all sorts of data sets in an acceptable manner. Due to this lack of previous ones, we developed a novel model employing the entropy-transformed function. We utilized the inverse Weibull model to function as the reference model to assess the applicability of the entropy transformation. The distribution, referred to as the “Entropy-Transformed Inverse Weibull Distribution” (ETIWL), is derived by applying the entropy transformation to the inverse Weibull model. The proposed distribution&apos;s core characteristics have been taken into account. The maximum-likelihood approach is used to estimate the parameters of the given distribution. Four real data sets are used in this study with the thorough simulation analysis to see whether the proposed distribution is superior.

  • 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

    Engineering Reports

  • ISSN

    2577-8196

  • e-ISSN

    2577-8196

  • Volume of the periodical

    7

  • Issue of the periodical within the volume

    7

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    23

  • Pages from-to

    "e70171"

  • UT code for WoS article

    001540811300048

  • EID of the result in the Scopus database

    2-s2.0-105011993854