A New Odd Beta Prime-Burr X Distribution with Applications to Petroleum Rock Sample Data and COVID-19 Mortality Rate

Autor: Ahmad Abubakar Suleiman, Hanita Daud, Narinderjit Singh Sawaran Singh, Aliyu Ismail Ishaq, Mahmod Othman
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Data, Vol 8, Iss 9, p 143 (2023)
Druh dokumentu: article
ISSN: 2306-5729
DOI: 10.3390/data8090143
Popis: In this article, we pioneer a new Burr X distribution using the odd beta prime generalized (OBP-G) family of distributions called the OBP-Burr X (OBPBX) distribution. The density function of this model is symmetric, left-skewed, right-skewed, and reversed-J, while the hazard function is monotonically increasing, decreasing, bathtub, and N-shaped, making it suitable for modeling skewed data and failure rates. Various statistical properties of the new model are obtained, such as moments, moment-generating function, entropies, quantile function, and limit behavior. The maximum-likelihood-estimation procedure is utilized to determine the parameters of the model. A Monte Carlo simulation study is implemented to ascertain the efficiency of maximum-likelihood estimators. The findings demonstrate the empirical application and flexibility of the OBPBX distribution, as showcased through its analysis of petroleum rock samples and COVID-19 mortality data, along with its superior performance compared to well-known extended versions of the Burr X distribution. We anticipate that the new distribution will attract a wider readership and provide a vital tool for modeling various phenomena in different domains.
Databáze: Directory of Open Access Journals