Bayesian Alpha-Mixture Survival Models

Implements Bayesian estimation for alpha-mixture survival models with right-censored data. Weibull-Weibull, Gamma-Weibull, and Lognormal-Lognormal component specifications are supported, with all component parameters treated as unknown. The package provides identifiability handling, adaptive Markov chain Monte Carlo sampling, convergence diagnostics, model comparison criteria, and posterior survival, hazard, and density estimation. The methodology extends the framework described by Luan et al. (2026) . Danish Ezwan, David Goldberg, and Ting Huang contributed equally to the package.