A New Probabilistic Approach: Estimation and Monte Carlo Simulation with Applications to Time-to-Event Data

Huda M. Alshanbari, Zubair Ahmad (), Hazem Al-Mofleh, Clement Boateng Ampadu and Saima K. Khosa
Additional contact information
Huda M. Alshanbari: Department of Mathematical Sciences, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia
Zubair Ahmad: Department of Statistics, Quaid-i-Azam University, Islamabad 44000, Pakistan
Hazem Al-Mofleh: Department of Mathematics, Tafila Technical University, Tafila 66110, Jordan
Clement Boateng Ampadu: Independent Researcher, 31 Carrolton Road, Boston, MA 02132, USA
Saima K. Khosa: Department of Mathematics and Statistics, University of Saskatchewan, Saskatoon, SK S7N 5E5, Canada

Mathematics, 2023, vol. 11, issue 7, 1-30

Abstract: In this paper, we propose a useful method without adding any extra parameters to obtain new probability distributions. The proposed family is a combination of the two existing families of distributions and is called a weighted sine- G family. A two-parameter special member of the weighted sine- G family, using the Weibull distribution as a baseline model, is considered and investigated in detail. Some distributional properties of the weighted sine- G family are derived. Different estimation methods are considered to estimate the parameters of the special model of the weighted sine- G family. Furthermore, simulation studies based on these different methods are also provided. Finally, the applicability and usefulness of the weighted sine- G family are demonstrated by analyzing two data sets taken from the engineering sector.

Keywords: Weibull model; trigonometric function; family of distributions; simulation; statistical modeling; engineering data (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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