A novel extended model with versatile shaped failure rate: Statistical inference with Covid -19 applications

Area of Science:

• Statistics
• Mathematical Modeling
• Epidemiology

Background:

• Statistical models are crucial for data analysis across diverse fields.
• There is a continuous need for novel statistical models to fit complex datasets.
• Accurate modeling of disease spread, like COVID-19, is vital for public health.

Purpose of the Study:

• To propose a new unique statistical model.
• To analyze the theoretical properties of the proposed model, including its density, quantile, and characteristic functions.
• To apply the novel statistical distribution to model COVID-19 mortality rates in specific countries.

Main Methods:

• Utilized modified Kies generalized transformation.
• Introduced a new power function to construct the statistical model.
• Investigated theoretical properties: density, quantile, characteristic functions, stochastic ordering, mean, and moments.
• Fitted the proposed distribution to COVID-19 mortality data.

Main Results:

• A novel statistical model was successfully developed.
• The linear illustration of the density function was presented and discussed.
• The model's theoretical properties were thoroughly analyzed.
• The proposed distribution demonstrated superior fit to COVID-19 mortality data in certain countries compared to existing models.

Conclusions:

• The novel statistical model offers a promising tool for data analysis.
• The developed distribution is particularly effective for modeling COVID-19 mortality rates.
• The new model shows potential for broader applications in epidemiological studies.