Properties, estimation, and applications of the extended log-logistic distribution

Autor:	Veronica Kariuki, Anthony Wanjoya, Oscar Ngesa, Amirah Saeed Alharthi, Hassan M. Aljohani, Ahmed Z. Afify
Jazyk:	angličtina
Rok vydání:	2024
Předmět:	Log-logistic distribution Alpha-power family Survival data Maximum likelihood estimation Order statistics Medicine Science
Zdroj:	Scientific Reports, Vol 14, Iss 1, Pp 1-34 (2024)
Druh dokumentu:	article
ISSN:	2045-2322
DOI:	10.1038/s41598-024-68843-4
Popis:	Abstract This paper presents the exponentiated alpha-power log-logistic (EAPLL) distribution, which extends the log-logistic distribution. The EAPLL distribution emphasizes its suitability for survival data modeling by providing analytical simplicity and accommodating both monotone and non-monotone failure rates. We derive some of its mathematical properties and test eight estimation methods using an extensive simulation study. To determine the best estimation approach, we rank mean estimates, mean square errors, and average absolute biases on a partial and overall ranking. Furthermore, we use the EAPLL distribution to examine three real-life survival data sets, demonstrating its superior performance over competing log-logistic distributions. This study adds vital insights to survival analysis methodology and provides a solid framework for modeling various survival data scenarios.
Databáze:	Directory of Open Access Journals
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