Analysis of COVID-19 and cancer data using new half-logistic generated family of distributions

• Autorzy: Khan Sadaf , Tahir Muhammad H. , Jamal Farrukh

Identyfikatory

DOI

10.37190/ord230405

• Języki publikacji: EN

Abstrakty

EN

We focus on a specific sub-model of the proposed family that we call the new half logistic-Fréchet. This sub-model stems from a new generalisation of the half-logistic distribution which we call the new half-logistic-G. The novelty of proposing this new family is that it does not include any additional parameters and instead relies on the baseline parameter. Standard statistical formulas are used to show the forms of the density and failure rate functions, ordinary and incomplete moments with generating functions, and random variate generation. The maximum likelihood estimation procedure is used to estimate the set of parameters. We conduct a simulation analysis to ensure that our calculations are converging with lower mean square error and biases. We use three real-life data sets to equate our model to well-established existing models. The proposed model outperforms the well-established four parameters beta Fréchet and exponentiated generalized Fréchet for some real- -life results, with three parameters such as half-logistic Fréchet, exponentiated Fréchet, Zografos–Balakrishnan gamma Fréchet, Topp–Leonne Fréchet, and Marshall–Olkin Fréchet and two-parameter classical Fréchet distribution.

Słowa kluczowe

EN

half-logistic distribution; generalized family; likelihood estimation; bio-medical data; Frechet distribution

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Operations Research and Decisions
• Rocznik: 2023
• Tom: Vol. 33, No. 4
• Strony: 71--95
• Opis fizyczny: Bibliogr. 20 poz., rys.

Twórcy

autor

Khan Sadaf

• Department of Statistics, The Islamia University of Bahawalpur, Punjab, Pakistan
• Department of Social and Allied Sciences, Cholistan University of Veterinary and Animal Sciences, Bahawalpur, Punjab, Pakistan

• https://orcid.org/0000-0002-0258-5124

autor

Tahir Muhammad H.

• Department of Statistics, The Islamia University of Bahawalpur, Punjab, Pakistan

• https://orcid.org/0000-0002-2157-3997

autor

Jamal Farrukh

• Department of Statistics, The Islamia University of Bahawalpur, Punjab, Pakistan

• https://orcid.org/0000-0001-6192-9890

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).