Supplementary file 1_Bell-generated family of mixture cure rate models with application to credit default.docx

To address these features, we propose a new class of mixture cure rate models based on the Bell-generated (Bell-G) class of distributions. By integrating the Bell-G mechanism with classical baseline distributions, including the Weibull, Burr XII, log-logistic, and lognormal, we develop flexible survival models capable of capturing complex hazard dynamics and tail behavior.

The proposed models naturally accommodate a cured fraction while offering enhanced flexibility in representing diverse distributional shapes. Parameter estimation is carried out using the maximum-likelihood method, and the finite-sample performance of the estimators is assessed via Monte Carlo simulations in terms of bias, root-mean-squared error and estimated cure proportions. Covariate effects on the cure fraction are incorporated via a logistic link function.