Modeling Maternal Blood Loss Using the Exponentiated Kumaraswamy–Inverse Lomax Distribution: Applications to Diverse Real-Life Data

Abstract

This study introduces the Exponentiated Kumaraswamy–Inverse Lomax (EK–IL) distribution as a flexible and robust statistical model for analyzing maternal blood loss during delivery. The proposed distribution effectively accommodates skewness and heavy-tailed behavior, which are common characteristics of clinical data. Model parameters are estimated using the maximum likelihood method, and the performance of the EK–IL distribution is evaluated through goodness-of-fit measures and information criteria. Comparative analyses demonstrate that the proposed model outperforms several well-known competing distributions. Further validation using four additional real datasets confirms the adaptability and robustness of the EK–IL distribution. The results suggest that the EK–IL model provides a powerful framework for medical data analysis and broader applications in applied statistics.