Marshall–Olkin Weibull–Burr XII distribution with application to physics data

Author:

Alsadat Najwan1ORCID,Nagarjuna Vasili B. V.2ORCID,Hassan Amal S.3ORCID,Elgarhy Mohammed45ORCID,Ahmad Hijaz678ORCID,Almetwally Ehab M.9

Affiliation:

1. 1 Department of Quantitative Analysis, College of Business Administration, King Saud University, P.O. Box 71115, Riyadh 11587, Saudi Arabia

2. Department of Mathematics Vellore Institute of Technology Andhra Pradesh 2 , Amaravati, India

3. Faculty of Graduate Studies for Statistical Research, Cairo University 3 , 5 Dr. Ahmed Zewail Street, Giza 12613, Egypt

4. Mathematics and Computer Science Department, Faculty of Science, Beni-Suef University 4 , Beni-Suef 62521, Egypt

5. 5 Department of Basic Sciences, Higher Institute for Administrative Sciences, Belbeis, AlSharkia, Egypt

6. Section of Mathematics, International Telematic University Uninettuno 6 , Corso Vittorio Emanuele II, 39,00186 Roma, Italy

7. 7 Near East University, Operational Research Center in Healthcare, Nicosia 99138, TRNC Mersin 10, Turkey

8. 8 Department of Computer Science and Mathematics, Lebanese American University, Beirut, Lebanon

9. 9 Department of Statistics, Faculty of Business Administration, Delta University for Science and Technology, Gamasa, Belqas 11152, Egypt

Abstract

The focus of this study is a new lifetime distribution with five parameters created by combining the Weibull–Burr XII model and the Marshall–Olkin-G family. The newly suggested model is known as the Marshall–Olkin Weibull–Burr XII (MOWBXII) distribution. The new distribution has the benefit of being able to model different types of data, and it is useful in reliability and lifespan statistics. Several current distributions as well as new distributions are included in the MOWBXII distribution. The MOWBXII density function is represented as a linear combination of Burr XII densities. Some statistical properties of the MOWBXII distribution are discussed. Various techniques for estimating the model’s parameters are used. The proposed estimation methods are weighted least squares, maximum likelihood, least squares, and maximum product of spacing methods. The effectiveness of different estimates is evaluated in terms of relative bias and mean squared error of the simulation study. Practical illustrations of the MOWBXII distribution are demonstrated using two real datasets. Furthermore, it is shown that the proposed distribution fits well, and this is claimed by comparing with Burr XII-based distributions and some other distributions by means of some measures of goodness-of-fit.

Funder

Deanship of Scientific Research, King Saud University

Publisher

AIP Publishing

Subject

General Physics and Astronomy

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