Applications of Generalised New Linear-Exponential Distribution in Biomedical Reliability Modelling
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Abstract
The accurate modelling of biomedical reliability is critical for understanding failure mechanisms in medical devices, biological systems, and healthcare interventions. Traditional lifetime distributions often lack the flexibility needed to capture complex hazard rate behaviors observed in biomedical data. This study introduces the application of the Generalised New Linear-Exponential (GNLE) distribution for enhancing biomedical reliability analysis. The GNLE distribution is an extension of the standard exponential family, designed to accommodate monotonic and non-monotonic hazard functions, which are frequently encountered in biomedical settings such as device wear-out and human survival studies. By integrating this distribution into the reliability modelling framework, the study demonstrates improved goodness-of-fit and predictive accuracy over conventional models such as the Weibull and Gamma distributions. The methodology includes formal definition, parameter estimation via maximum likelihood, and application to real-world biomedical datasets, including pacemaker failure and post-operative survival rates. Numerical examples validate the theoretical propositions, while graphical diagnostics substantiate the enhanced performance of GNLE models in capturing biomedical system behavior. The results indicate that GNLE provides a robust statistical tool for biomedical reliability modelling, contributing to better risk assessment, decision-making, and public health outcomes.