ambs: 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) <doi:10.3390/math14101772>.
Danish Ezwan, David Goldberg, and Ting Huang contributed equally to the
package.
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