A New Extended Chen Distribution for Modelling COVID-19 Data
Author Information
Author(s): Alghamdi Amani S., Alnaji Lulah
Primary Institution: King Abdulaziz University, Jeddah, Saudi Arabia
Hypothesis
The study proposes a new flexible statistical distribution to model COVID-19 data more effectively than existing models.
Conclusion
The Topp-Leone Exponentiated Chen distribution provides a more accurate and flexible approach to modeling real-world phenomena, particularly COVID-19 data.
Supporting Evidence
- The TLEC distribution outperformed existing models in terms of goodness-of-fit metrics.
- Simulation studies demonstrated the efficiency of maximum likelihood estimation for the TLEC distribution.
- The TLEC distribution can capture various hazard rate shapes, making it valuable for survival analysis.
Takeaway
This study introduces a new way to understand COVID-19 data using a special math formula that can fit different patterns better than older methods.
Methodology
The study derives key statistical properties of the new distribution and applies maximum likelihood estimation to real COVID-19 data.
Limitations
The TLEC distribution was only applied to univariate data, and its performance in multivariate contexts remains unexplored.
Digital Object Identifier (DOI)
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