Theory, simulation, and application of the entropy transformation of the Chen distribution to enhance interdisciplinary data analysis

This study introduces a novel model that integrates the Chen distribution with entropy transformation techniques to enhance cross-disciplinary data analysis. The Chen distribution, known for its applicability in medical and engineering longevity studies, is extended through entropy-based transformations to capture diverse data patterns. The proposed model's key statistical properties, including reliability functions, hazard rates, and moments, are thoroughly derived. We explore the flexibility of the new density and hazard rate functions, highlighting their ability to represent various data structures. Parameter estimation is conducted using simulated data, and the model's performance is rigorously assessed through goodness-of-fit criteria. Comparative analysis with several well-established models across four real-world lifespan datasets from engineering and medical fields shows that the proposed model delivers superior fit and adaptability, underscoring its practical utility.