Modeling Aging Based on Semiparametric Starshaped Mean Equilibrium Life Model: A Bayesian Approach

Music City Center 

This study introduces a novel semiparametric regression model based on the starshaped mean equilibrium life (SMEL) function to describe the mean remaining life of aging systems. The SMEL function, exhibiting a decreasing-then-increasing pattern, provides a flexible framework for modeling non-monotonic aging behaviors. Addressing the challenge of non-identifiability of the survival function, we propose a nonparametric testing procedure to validate the starshaped assumption. An adaptive semiparametric MCMC algorithm is developed to estimate regression parameters and select optimal priors, ensuring robust Bayesian regularization. Validated through simulations and real-world applications, the methodology effectively captures complex aging patterns, offering actionable insights for reliability analysis, survival modeling, and decision-making in healthcare, engineering, and actuarial science. This work bridges semiparametric regression, Bayesian inference, and nonparametric testing, advancing the theoretical and computational foundations of aging modeling.

Semiparametric Regression

Mean Equilibrium Life Function

Bayesian Inference

Nonparametric Testing

Aging Modeling

Starshaped Function 

Section on Nonparametric Statistics