Neutrosophic Quasi-XLindley distribution with applications of  COVID-19 data

Rehab Alsultan; Amer Ibrahim Al-Omari

Authors

Rehab Alsultan Department of Mathematical Sciences, Umm Al-Qura University, Makkah 24382, Saudi Arabia,
Amer Ibrahim Al-Omari Department of Mathematics, Faculty of Science, Al al-Bayt University, Mafraq 25113, Jordan

Keywords:

Neutrosophic; COVID-19; Maximum likelihood estimation; Probability distribution; Quasi-XLindley distribution, Uncertainty

Abstract

The Quasi-XLindley distribution (QXLD) is widely used in the field of survival and
reliability engineering to simulate lifespan data in different fields of human, electronic designs and
other fields. However, when dealing with uncertain data, a more generalized version of this
distribution is needed. To address this, a neutrosophic Quasi-XLindley distribution (NQXLD) is
developed in this paper. The NQXLD is particularly useful for representing skewed uncertain data.
In this study, we present some statistical characteristics of the NQXL distribution, including the
neutrosophic mean time failure, neutrosophic hazard rate, neutrosophic moments, and
neutrosophic survival function. We also evaluate the parameters using the maximum likelihood
(ML) estimation technique in a neutrosophic context based on a simulation study. Finally,
applications of three different real data sets are considered to investigate the applicability of the
suggested NQXL distribution. The results show the flexibility of the NQXL distribution in fitting
various types of COVID-19 data as compared to the QXLD.

DOI: 10.5281/zenodo.15009487