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, Saima K. Khosa
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.