Introducing the new arcsine-generator distribution family: An in-depth exploration with an illustrative example of the inverse weibull distribution for analyzing healthcare industry data

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F24%3A10256402" target="_blank" >RIV/61989100:27740/24:10256402 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.sciencedirect.com/science/article/pii/S1687850724000633" target="_blank" >https://www.sciencedirect.com/science/article/pii/S1687850724000633</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.jrras.2024.100879" target="_blank" >10.1016/j.jrras.2024.100879</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Introducing the new arcsine-generator distribution family: An in-depth exploration with an illustrative example of the inverse weibull distribution for analyzing healthcare industry data

Popis výsledku v původním jazyce

The study is about a novel Arcsin-function based generator of new families of distributions. We chose the inverse Weibull distribution as the reference distribution to see if the generator could be employed. This generator helps for developing a distribution called the novel Arcsin inverse Weibull. The main features of the suggested distribution have been taken into account. Some of the indicators used in this class include the density function, complete and incomplete moments, average deviation, and aging indicators. The model&apos;s parameters are determined using the maximum likelihood method in both simulations and data analysis. The effectiveness of the suggested model in the healthcare sector is demonstrated by analyzing five sets of data, revealing its superior fit compared to the traditional inverse sine model, which is associated with the inverse Weibull model.

Název v anglickém jazyce

Introducing the new arcsine-generator distribution family: An in-depth exploration with an illustrative example of the inverse weibull distribution for analyzing healthcare industry data

Popis výsledku anglicky

The study is about a novel Arcsin-function based generator of new families of distributions. We chose the inverse Weibull distribution as the reference distribution to see if the generator could be employed. This generator helps for developing a distribution called the novel Arcsin inverse Weibull. The main features of the suggested distribution have been taken into account. Some of the indicators used in this class include the density function, complete and incomplete moments, average deviation, and aging indicators. The model&apos;s parameters are determined using the maximum likelihood method in both simulations and data analysis. The effectiveness of the suggested model in the healthcare sector is demonstrated by analyzing five sets of data, revealing its superior fit compared to the traditional inverse sine model, which is associated with the inverse Weibull model.

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

2024

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

17

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

20

Strana od-do

1-20

Kód UT WoS článku

001290968400001

EID výsledku v databázi Scopus

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