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

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 fami...

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Bibliographic Details
Published inMathematics (Basel) Vol. 11; no. 7; p. 1583
Main Authors Alshanbari, Huda M., Ahmad, Zubair, Al-Mofleh, Hazem, Ampadu, Clement Boateng, Khosa , Saima K.
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.04.2023
Subjects
Behavior
engineering data
Estimation theory
Event history analysis
family of distributions
Mathematical models
Mathematical research
Mathematics
Methods
Monte Carlo method
Monte Carlo simulation
Parameters
Probabilistic number theory
Random variables
simulation
Software
Statistical analysis
statistical modeling
trigonometric function
Weibull distribution
Weibull model
Pakistan
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Summary: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.
ISSN:2227-7390
2227-7390
DOI:10.3390/math11071583