A General Framework for Bayesian Estimation Using the 'Tierney'-'Kadane' Approximation // Provides a distribution- independent framework for Bayesian estimation of arbitrary univariate probability models using the 'Tierney'-'Kadane' approximation ('Tierney' 'Kadane', 1986 doi:10.1080/01621459.1986.10478240). Users specify the probability distribution, likelihood, prior distributions, and censoring mechanism, while the package automatically constructs the posterior distribution, computes posterior modes and Hessian matrices, approximates posterior expectations under several Bayesian loss functions, and returns Bayesian parameter estimates, posterior covariance matrices, credible intervals, diagnostic plots, and model comparison statistics. Supports complete, right-, left-, interval-, Type-I, Type-II, progressive Type-II, hybrid, and doubly censored data ('Lawless', 2003 ISBN:978-0-471-37215-8; 'Meeker' 'Escobar', 1998 ISBN:978-0-471-14328-4; 'Balakrishnan' 'Aggarwala', 2000 ISBN:978-0-8176-4129-0; 'Kundu' 'Pradhan', 2009 doi:10.1198/TECH.2009.0019), making it a flexible tool for Bayesian reliability, survival, and lifetime data analysis.